In an era of rapid technological advancement, the dynamic interplay between Artificial Intelligence (AI) and Human Intelligence (HI) is shaping the future of education. As we peer into the horizon, it becomes increasingly clear that our approach to preparing the next generation for the challenges and opportunities that await must evolve. Here, we explore how AI and HI are set to play harmonious, complementary roles in the realm of preschool education and beyond.

Before we embark on this educational journey, it is crucial to envision the future professions that will shape the educational landscape. Two significant examples illustrate the evolving role of AI in various fields:

Future-proofing students for a rapidly evolving world equips students to be both AI-competent and distinctly human.

The collaboration between AI and human educators forms the core of the new educational landscape. This symbiotic relationship aims to merge the precision and efficiency of AI with the empathetic and creative guidance provided by human mentors. Heres how this partnership is poised to revolutionize education:

The integration of AI in preschool education unfolds a unique paradigm where young children can seamlessly transition between the roles of the tutee and the tutor, fostering a multifaceted and enriching educational experience. This concept manifests in three distinct applications of AI in education: as a tutor, as a tutee, and as a tool.

In essence, this multifaceted interaction with AI establishes a symbiotic relationship where the roles of teacher and student are fluid. By seamlessly transitioning between these roles, preschool children not only benefit from tailored guidance but also actively engage with AI as a creative collaborator and a student, cultivating a well-rounded skill set that extends beyond conventional learning approaches.

In summary, the future of education hinges on the collaborative efforts of human educators and AI. Together, they create an educational ecosystem that leverages the strengths of each, ensuring that students are not only equipped with knowledge but also possess the essential skills and attributes needed to thrive in a future where human qualities play a pivotal role.

Dr. Richard Yen, Harvard University PhD, founder of Ednovation, which develops edtech and operates Cambridge, ChildFirst, and Shaws Preschools in Singapore, South East Asia, and China.

TNGlobal INSIDERpublishes contributions relevant to entrepreneurship and innovation. You maysubmit your own original or published contributionssubject to editorial discretion.

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There's more to AI than Nvidia. This is why the Robo Global Artificial Intelligence ETF (NYSEARCA:THNQ) is an interesting way for investors to access artificial intelligence and robotics. What I like about the fund is that it's very well diversified, making it a pure thematic play beyond the idiosyncratic aspect of just a select number of stocks in the space.

THNQ seeks to track the ROBO Global Artificial Intelligence Index. This index aims to track companies that generate a significant portion of their revenues from the AI market. THNQ offers a diversified strategy for investors, providing exposure to the very best public companies from around the globe, irrespective of their size and location. The fund serves as an excellent platform for investors to capitalize on the expected growth in AI and robotics, sectors that are transforming virtually every industry across the globe.

THNQ strives for a balance between growth and value, focusing on companies with strong business models and positive cash flows. The fund is rebalanced on a quarterly basis to ensure it consistently holds the most innovative and promising companies in the AI and robotics sectors. The ETF is not limited to technology companies; it also includes firms from the consumer cyclical, communication, and healthcare sectors, among others. Geographically, THNQ's holdings are diverse, with significant exposure to non-U.S. markets, particularly in Europe and East Asia.

ycharts.com

I mentioned at the start of the writing that this is a well-diversified fund. No holding currently makes up more than 2.71% of the fund, and crowd favorite Nvidia is currently ranked 8 in the top 10. Again - I very much like this. It makes this a far more nuanced and diversified way of playing AI than other products where Nvidia is the biggest holding.

roboglobaletfs.com

The sector composition of THNQ is diverse, ensuring that investors gain exposure to various segments of the economy. As you'd expect, the majority of the fund is in the Technology space, but it's not a pure tech fund in that it does have stocks from non-tech groups.

ycharts.com

When comparing THNQ to its peers, it's important to note that it outperformed the TrueShares Technology, AI & Deep Learning ETF (LRNZ) which is another fund in the space. LRNZ is considerably less diversified with top holdings having more concentration risk than THNQ.

stockcharts.com

Investing in AI and robotics comes with its share of advantages and potential risks.

On the positive side, these sectors are experiencing unprecedented growth due to advancements in technology and increasing adoption across different industries worldwide. Furthermore, AI and robotics offer substantial potential for innovation, making them attractive sectors for forward-thinking investors.

On the flip side, investing in AI and robotics also carries risks. These include regulatory uncertainties, privacy concerns, and potential job displacements due to automation. Moreover, these sectors are highly competitive, requiring constant innovation and substantial capital expenditure.

Personally, I think THNQ is a solid avenue for investors looking to gain exposure to the rapidly growing fields of AI and robotics. It's well diversified, and if you believe that AI is unstoppable, despite relatively weak performance as of late, this becomes a good fund to access the trend.

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Robo Global Artificial Intelligence ETF: A Diversified AI Play (THNQ) - Seeking Alpha

One activation method that opens up a great many possibilities for different functional groups, at least on paper, is borylation. In this process, a chemical group containing the element boron is bonded to a carbon atom in the scaffold. The boron group can then simply be replaced by a whole range of medically effective groups.

"Although borylation has great potential, the reaction is difficult to control in the lab. That's why our comprehensive search of the worldwide literature only turned up just over 1,700 scientific papers on the subject," Atz says, describing the starting point for his work.

The idea was to take the reactions described in the scientific literature and use them to train an AI model, which the research team could then use to consider new molecules and identify as many sites as possible on them where borylation would be feasible. However, the researchers ultimately fed their model only a fraction of the literature they found. To ensure that the model wasn't misled by false results from careless research, the team limited itself to 38 particularly trustworthy papers. These described a total of 1,380 borylation reactions.

To expand the training dataset, the team supplemented the literature results with evaluations of 1,000 reactions carried out in the automated laboratory operated by Roche's medicinal chemistry research department. This allows many chemical reactions to be carried out at the milligram scale and analysed simultaneously. "Combining laboratory automation with AI has enormous potential to greatly increase efficiency in chemical synthesis and improve sustainability at the same time," says David Nippa, a doctoral student from Roche who accomplished the project together with Atz.

The predictive capabilities of the model generated from this data pool were verified using six known drug molecules. In five out of six cases, experimental testing in the laboratory confirmed the predicted additional sites. The model was just as reliable when it came to identifying sites on the scaffold where activation isn't possible. What's more, it determined the optimum conditions for the activation reactions.

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Artificial intelligence finds ways to develop new drugs - Mirage News

HyperCycle is a decentralized network that connects AI machines to make them smarter and more profitable. It enables companies of all sizes to participate in the emerging AI computing economy.

Artificial intelligence (AI) is a rapidly evolving field that seems likely to fall into the hands of major companies or organizations with nationally driven budgets. One might think that only these have the massive financial resources to generate the computing power to train and ultimately own AI.

Recent events at OpenAI, a developer of the AI chatbot ChatGPT, highlight the challenges of centralized AI development. The firing of CEO Sam Altman and the resignation of co-founder Greg Brockman raise questions about governance and decision-making in centralized AI entities and highlight the need for a more decentralized approach. Srinivasan Balaji, a former chief technology officer at Coinbase, has become a staunch proponent for increased transparency in the realm of AI, advocating for the adoption of decentralized AI systems.

In addition to centralization, theres a lot of fragmentation in the AI space, meaning cutting-edge systems are unable to communicate with one another. Moreover, a high degree of centralization brings considerable security risks and reliability issues. Plus, given the vast amounts of computing power needed, efficiency and speed are key.

To achieve the full potential of AI that answers to all of humanity, we need a different approach one that decentralizes AI and allows AI systems to communicate with each other, eliminating the need for intermediaries. This would increase AI systems time to market, intelligence and profitability. While many systems are currently specialized in specific tasks, such as voice or facial recognition, a future shift to artificial general intelligence could allow one system to undertake a wide range of tasks simultaneously by delegating those tasks to multiple AIs.

As mentioned above, currently, the AI industry is dominated by large corporations and institutional investors, making it difficult for individuals to participate. HyperCycle, a novel ledgerless blockchain architecture, emerges as a transformative solution, aiming to democratize AI by establishing a fast and secure network that empowers everyone, from large enterprises to individuals, to contribute to AI computing.

HyperCycle is powered by a layer 0++ blockchain technology that enables rapid, cost-effective microtransactions between diverse AI agents interconnected to each other, and collectively solving problems.

This internet of AIs allows systems to interact and collaborate directly without intermediaries. It addresses the challenges of overcoming the slow, costly processes of the siloed AI landscape.

This is particularly timely, as the number of machine-to-machine (M2M) connections globally is increasing rapidly.

For instance, existing companies could interact with HyperCycles AIs specializing in IoT, blockchain, and supply chain management to optimize logistics for clients, predict maintenance before breakdowns occur, and ensure seamless data integrity. By enabling this interconnected ecosystem of decentralized A Is, HyperCycle can lead to operational efficiency and innovation in service offerings.

HyperCycle has also partnered with Penguin Digital to create HyperPG, a service that connects all the network beneficiaries together. HyperPG uses Paraguays abundant hydropower to provide a green and efficient source of energy for AI computing.

One of HyperCycles key features is the HyperAiBox, a plug-and-play device that allows individuals and organizations to perform AI computations at home and reduces their reliance on large corporations with vast data centers. The compact box is about the size of a modem, has a touchscreen, and allows nodes to be operated from home and network participants to be compensated for the resources they provide to the network. It is also a low-power solution.

The launch of HyperCycles mainnet, ahead of schedule, highlights the networks rapid growth. Currently, over 59,000 initial nodes are providing Uptime to the network by covering operational expenses. An additional 230,000 single licenses will soon join the ecosystem. This expansion indicates a strong demand for over 295 million HyPC tokens, reflecting the networks engagement and growth.

The three key metrics of Uptime, Computation, and Reputation incentivize node operators to maintain high standards, ensuring a stable, secure, and decentralized network environment.

Since June 2023, HyperCycles network has been operational, scaling up as demand increases. Source: HyperCycle

AI remains at a nascent stage, but HyperCycles goal is to anticipate the challenges that might stand in this technologys way and break down barriers to entry, making AI more accessible and affordable to everyone.

Disclaimer. Cointelegraph does not endorse any content or product on this page. While we aim at providing you with all important information that we could obtain in this sponsored article, readers should do their own research before taking any actions related to the company and carry full responsibility for their decisions, nor can this article be considered as investment advice.

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JPMorgans asset management division employs 1300 portfolio managers and research analysts globally across stocks, bonds, derivatives and alternative asset classes, with $US400 million a year invested into technology to leverage AI and machine learning models.

That hasnt stopped JPMorgans rivals from also investing, with a PwC global asset management survey showing that more than 90 per cent of investment firms are already using disruptive technology such as AI within their business.

On AI, we decided a long time ago to build our own tech and not rent someone elses, Mr Gatch said. I think thats now a competitive advantage for our portfolio managers and clients.

The global market for AI in asset management is estimated to be worth about $US2.6 billion in 2022 and is expected to expand at a compound annual growth rate of 24.5 per cent over the next seven years, according to one estimate by US firm Grand View Research.

Earlier this year BlackRock, the worlds largest asset manager, described AI in its mid-year investment outlook as a mega force trend that would help unlock the value of the data gold mine some companies may be sitting on.

Elsewhere, JPMorgan is among a slew of investment banks, including Macquarie, that are launching more ETF products into the Australian market to challenge the dominance of BlackRock, Vanguard and State Street.

Mr Gatch said the global ETF industry had attracted $US1.4 trillion of funds in 2022, versus $US700 billion for traditional investment funds unlisted on exchanges.

In Australia, data from Betashares shows the local ETF industry recorded $13.5 billion of net inflows last year, versus outflows of $26.8 billion from unlisted managed funds.

JPMorgans strategy to grab market share is to offer so-called active ETFs that may outperform the traditional index-tracking products. The firm forecasts active ETF inflows to grow at a 40 per cent annual rate for the next five years, compared to 17 per cent for indexed ETFs.

That has big implications for how we run our business and whats happening is fairly astonishing, Mr Gatch added.

The story is no longer about indexing, we think that [active] will drive a wave of dramatic growth into the industry.

The JPMorgan Equity Premium Income Product is said to have attracted more inflows than any other ETF in 2023, with net assets of around $US29 billion in November. Much of its popularity is due to an active strategy of selling call options that provide extra income if the market falls or tracks sideways.

On fees, the CEO said asset managers, including the ETF sector, remained under pressure, but JPMorgans investment in digital currency and blockchain technology could eventually bring costs down.

Were doing a bunch of stuff on blockchain, he said. We have working groups looking at tokenisation for private markets, how to improve liquidity between institutions for private credit. Its going to take time, but weve got smart people, and operational efficiency is important.

As for JPMorgan launching a bitcoin ETF, its not on the agenda anytime soon. No, weve not done [regulatory] filings.

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JPMorgan's George Gatch says artificial intelligence gives them firm ... - The Australian Financial Review

A National Transportation Safety Board investigation into a 2022 fatal crash inNorth Las Vegas, Nevada, that resulted in nine fatalities has given the board an excuse to recommend a new requirement for intelligent speed assistance technology in all new cars.

The board issued the recommendations earlier this month at a public meeting after determining the crash was caused by high speed, drug-impaired driving, and Nevadas failure to deter one drivers speeding recidivism due to systemic deficiencies, despite numerous speeding citations.

Intelligent speed assistance technology, or ISA, uses a cars GPS location compared with a database of posted speed limits and its onboard cameras to either issue a warning to drivers or to throttle back speed.

Passive ISA systems warn a driver when the vehicle exceeds the speed limit through visual, sound, or haptic alerts, and the driver is responsible for slowing the car.

Active systems include mechanisms that make it more difficult, but not impossible, to increase the speed of a vehicle above the posted speed limit and those that electronically limit the speed of the vehicle to fully prevent drivers from exceeding the speed limit.

This crash is the latest in a long line of tragedies weve investigated where speeding and impairment led to catastrophe, but it doesnt have to be this way, said NTSB Chair Jennifer Homendy. We know the key to saving lives is redundancy, which can protect all of us from human error that occurs on our roads. What we lack is the collective will to act on NTSB safety recommendations.

Homendy is a Democrat who served more than 14 years as Democratic staff director for the Subcommittee on Railroads, Pipelines, and Hazardous Materials of the Committee on Transportation and Infrastructure in the U.S. House of Representatives. She worked for the International Brotherhood of Teamsters, AFL-CIO, and American Iron and Steel Institute.

Eliminating speeding through the use of federally mandated speed limiters built into cars is a priority for the NTSB, which seeks to Develop performance standards for advanced speed-limiting technology, such as variable speed limiters and intelligent speed adaptation devices, for heavy vehicles, including trucks, buses, and motorcoaches. Then require that all newly manufactured heavy vehicles be equipped with such devices.

In 2021, speeding-related crashes resulted in 12,330 fatalitiesabout one-third of all traffic fatalities in the United States, the NTSB said.

However, according to the latest figures from AAA, 245 million drivers made a total of 229 billion driving trips, spent 91 billion hours driving, and drove 2.92 trillion miles in 2021. That means out of every 91 million hours of driving, there are 12,330 fatalities, or one fatality for every 7.3 million hours of driving.

According to the National Safety Council, the rates of fatal car accidents has greatly improved over the decades. This is due, in part, to the numerous safety features now required in cars, such as seatbelts, air bags, and backup cameras, which were mandated in 2018.

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Artificial Intelligence (AI) and automation have had a profound impact on the field of engineering. These technologies have the potential to revolutionise the way engineers design, analyse, and optimise systems and processes. However, it's important to note that while AI and automation offer tremendous benefits, they also come with challenges, including ethical considerations, job displacement concerns, and the need for robust cyber security. Engineers and organisations need to carefully plan and implement these technologies to maximise their advantages while addressing potential drawbacks.

The emergence of Artificial Intelligence (AI) in engineering has been a transformative development that has significantly impacted various engineering fields. AI technologies, such as machine learning and deep learning, have been applied to engineering tasks to enhance efficiency, accuracy, and innovation. Machine learning will be among the top engineering talents in demand in 2022. Learning how to incorporate AI into processes is already in demand due to engineers' extraordinary capacity for solving complicated challenges.

90% of major corporations are thought to have made some kind of investment in artificial intelligence (AI) technologies. Less than 15% of these firms, however, are currently using AI in their working environment. AI is one of the technologies with the quickest growth in the engineering industry. Even while there has always been some worry that AI may eliminate some occupations, the current state of affairs is that new technology is creating a variety of chances for engineering skills.

AI is used in manufacturing at many phases of the production process to increase productivity, accuracy, and automation. It uses machine learning, data analysis, and algorithms to let robots do tasks that once required direct human interaction. Utilising characteristics like predictive maintenance, quality control, process enhancement, and others, this technology boosts output and decreases downtime. By analysing vast amounts of data in real-time, AI-driven systems can make sensible decisions, optimise processes, and identify trendspeople would miss.

AI and automation have significant advantages for businesses since they can increase production, efficiency, and financial performance. Enhanced Productivity Enhanced Efficiency, Improved Data Analysis and More favourable bottom-line results are some major advantages. However,there are also many challenges in developing and using AI for automotive electronics, including complexity, dependability, security, and regulation.

AI algorithms can be used to analyse sensor data from structures, such as temperature and vibration data, to forecast when maintenance is necessary,and to spot warning indications of structural breakdown before they materialise. AI-powered cameras are used for inspection and surveillance. Artificial intelligence-driven structural analysis systems may simulate and assess complicated structural behaviour, assisting engineers in locating possible weak points, foretelling failure modes, and improving structural performance. By quickly adapting to user preferences, AI-powered optimisation attempts to improve the personalisation, cost-effectiveness, and utility of digital experiences. With the help of this technology, organisations can make data-driven decisions that enhance the functionality of their websites, user engagement, and rates of conversion.

Machine Learning (ML) optimises energy efficiency models, predicting the consumption of energy tools. Over the last five years, ML techniques gained traction in designing energy-efficient systems amid rising demand for technologies like smart buildings and IOTs (Internet of Things). Sustainable growth in smart cities relies on technological advancements, merging sustainability with energy efficiency. Artificial Intelligence (AI) plays a vital role in managing, coordinating, and forecasting electricity supply. The global push for a low-carbon transition amplifies the significance of AI in achieving energy goals. AI-driven "smart consumption" transforms energy usage patterns, enabling decentralised power grids for balanced energy flows.

Systems with artificial intelligence (AI) can be used to identify and detect traffic events such asaccidents, wrong-way driving, speeding, or roadblocks. Real-time traffic data is analysed using AI from a variety of cameras and IoT devices, including cars, buses, and even trains. As over 90% of accidents are the result of human error, it is anticipated to drastically reduce the number of accidents. AVs (Autonomous Vehicles) can lower the cost of travel. For instance, AVs will save labour expenses when used in public transportation. With smart carpooling, costs can be further reduced. By removing the need for human drivers, a driverless car might significantly ease traffic congestion. This may lead to a significant increase in car sharing, which would reduce the number of vehicles on the road and the overall carbon footprint compared to more conventional modes of transportation.

Integrating AI and automation into engineering processes offers numerous benefits, such as increased efficiency, improved accuracy, and cost reduction. However, it also presents several challenges and ethical considerations like safety and reliability, Algorithm Complexity, Human-AI Collaboration, Integration with Existing Systems and Ethical Considerations (data collection, privacy, and decision-making). Concerns about job displacement and human-AI collaboration have been growing as artificial intelligence and automation technologies continue to advance. These concerns centre on the potential for AI and automation to replace human workers in various industries, leading to job loss and economic disruption. However, it's important to note that these concerns are not without nuance, and there are also opportunities for collaboration between humans and AI that can lead to more productive and fulfilling work environments.

Digital twins, virtual replicas of physical entities, leverage real-time data, simulation, analytics, and visualisation. Enhancing decision-making, they cut costs and boost efficiency. Manufacturers benefit by integrating digital twins seamlessly, reducing expenses and accelerating value. Architects and engineers employ digital twins in building design, incorporating details on use, materials, and maintenance. This streamlines construction oversight and communication, ensuring better quality.

AI-driven maintenance prediction is transforming asset management, using historical data and real-time analysis to predict equipment failures and facilitate proactive maintenance. By identifying flaws and analysing behavioural patterns, AI recommends optimal times for replacements or repairs, reducing emergency repairs. In various industries, AI enhances data analytics, offering valuable insights into market trends, client preferences, and business strategies. AI-generated maintenance schedules prevent over-maintenance and minimise breakdowns, conserving resources. For example, AI monitors machinery spindles in milling operations, reducing the need for costly repairs. This innovative approach optimises efficiency and minimises wasteful spending.

AI systems face risks such as adversarial machine learning attacks, where attackers manipulate input data to alter the model's output, potentially leading to poor decision-making and security vulnerabilities. Privacy concerns revolve around the increased likelihood of data breaches and unauthorized access to personal information. With the vast amount of data being collected, there's a risk of misuse through hacking or security flaws. Organizations must regularly assess their infrastructure's security, identify vulnerabilities, and prioritize corrections to safeguard against cyber threats. This involves timely application of security patches, software and hardware updates, and implementation of robust security configurations.

Designing AI systems with human factors in mind is crucial to ensure usability, safety, and user acceptance. User experience considerations play a pivotal role in AI-integrated engineering solutions, as they directly impact how users interact with and perceive AI technologies. It not only improves the usability, safety, and acceptance of AI but also helps avoid potential pitfalls and negative consequences associated with poorly designed systems. By prioritising user experience considerations, AI engineers can create solutions that are not only technically proficient but also genuinely beneficial and user-friendly. Designing AI systems that complement human capabilities rather than replace them is very significant. When users see AI as a helpful tool that enhances their work, they are more likely to accept and use it.

In the past, it was believed that AI would eventually displace workers. Organisations observe that AI is expanding export opportunities and building a highly qualified workforce. Additionally, as automation and AI can now finish the fundamental and monotonous duties, engineering roles can concentrate more on activities that bring value, making engineering employment much more dynamic and fulfilling.

The future advancements of AI and automation in engineering hold immense promise, with several exciting trends and developments on the horizon like aerospace, electronics, energy storage, etc. Quantum algorithms can also be used for tasks like molecular modelling, optimising supply chains, and solving complex equations in real time. Generative design, powered by AI, is transforming how engineers approach product design. This can lead to highly efficient and innovative designs in various industries, including automotive and architecture. We can expect to see more autonomous drones, self-driving vehicles, and robotic systems in manufacturing and logistics. These technologies will improve efficiency, safety, and precision in various engineering applications.

It's important to note that while these advancements offer numerous benefits, they also come with challenges, including ethical concerns, cyber security risks, and the need for up-skilling the workforce. Engineers and organisations should stay informed and adapt to these emerging technologies to harness their full potential while addressing associated challenges.

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Artificial Intelligence and Automation in Engineering - Drishti IAS

CINCINNATI Artificial intelligence is creating a new way for individuals to learn about the Holocaust.

At the Nancy and David Wolf Holocaust & Humanity Center, the Dimensions in Testimony exhibit features testimony from Pinchas Gutter, a man now living in Canada but who spent time in six Nazi concentration camps as a young boy.

Visitors can ask him questions about his experience, how he feels about being a hologram, his favorite foods, his message to young people and pretty much anything else they can think of.

Gutter sat for several full days of recording. Artificial intelligence is used to understand questions and retrieve the most appropriate responses.

Holland Rains/WCPO

Because the algorithm pulls only from the testimony of the survivor, there is no risk for hallucination, which is when an AI model generates false or misleading information, museum representatives said.

Al Miller, a Jewish resident of Hamilton, Ohio, escaped Nazi Germany in 1937. He returned to Germany for the U.S. Army to interrogate suspected war criminals as a Ritchie Boy.

Last year, at the age of 100, Miller recorded his testimony for five full days of recordings. His daughter-in-law, Barbara Miller, who is also on the board of the museum, said this type of technology is a significant development for Holocaust education.

Theres almost nothing more important we can do than to share these stories, she said. Young people, in particular, many of whom know nothing about the Holocaust, need to be educated.

A December 2023 YouGov pollfound 20% of young people strongly agree or tend to agree that the Holocaust is a myth.

Barbara said Al found it important to share his story, no matter the crowd size: As long as he could make an impact and talk to them and inspire them, he felt he had done his job.

The museum said Als testimony, along with survivor and retired University of Cincinnati professor Henry Fenichel, will be available in early 2025.

Barbara Miller said that Al's message was always the same: "The Holocaust didn't start with bullets, it started with words."

She said she's worried that is something that is coming to fruition in the United States. The Anti-Defamation League has reported an increase in antisemitic incidents following Hamas' surprise attack in Israel on October 7, 2023.

Various artifacts from Millers experience are featured throughout the museum. Barbara said those items will be enhanced by museum guests getting an opportunity to speak with him.

Al had a tremendous sense of giving back. And he really wanted to ensure that the lessons of the Holocaust would not repeat, she said.

His efforts will continue.

Kara Driscoll, Director of Marketing & Events at Holocaust & Humanity Center said data shows that students, often digital natives, feel more comfortable interacting with this technology than they might talking to someone across from them.

This technology allows us to interact with their stories, their biographies, and keep their memories alive in an interactive way that is really meaningful to the visitors that experience it, she said.

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'There's almost nothing more important': Local Holocaust survivors living on through artificial intelligence - WCPO 9 Cincinnati

An artificial intelligence model showed promise in predicting ovarian cancer outcomes.

An artificial intelligence model called IRON (Integrated Radiogenomics for Ovarian Neoadjuvant therapy) shows an 80% accuracy rate in the prediction of therapy outcomes for patients with ovarian cancer. The artificial intelligence model focuses specifically on the volumetric reduction of tumor lesions within this patient population, according to a press release.

This tool surpassed the efficiency of present clinical methods, as IRON uses an approach that focuses on a patients liquid biopsy (cancer-specific information that can be observed via blood tests), overall health characteristics such as age, health status, tumor markers and disease images that were captured during CT scan images.

A recent research study, which was featured in Nature Communications, focused on 134 patients who had been diagnosed with high-grade ovarian cancer. Dr. Evis Sala, chair of Diagnostic Imaging and Radiotherapy at the Faculty of Medicine and Surgery of the Catholic University and Director of the Advanced Radiology Center at the Policlinico Universitario A. Gemelli IRCCS ran the study and the AI model was created by Professor Salas team at the University of Cambridge.

"We compiled two independent datasets with a total of 134 patients (92 cases in the first dataset, 42 in the second independent test set)," Sala and Dr. Mireia Crispin Ortuzar from Cambridge said in the press release.

When it comes to a precise accuracy rate in high-grade ovarian carcinoma, therapy response predictions result to about 50% accuracy. As there were a few significant biomarkers used for this type of cancer, the IRON model was able to predict chemotherapy responders more accurately.

Notably, this is not the first study showing that artificial intelligence has the potential to predict cancer outcomes. Earlier this year, research found that artificial intelligence may help determine which patients with prostate cancer were more likely to benefit from hormone therapy plus radiation. Additionally, another group of researchers also showed that artificially intelligence may play a role in diagnosing sarcopenia in patients with head and neck cancer.

Within the study, demographic information, treatment details, blood biomarkers (CA-125, which could indicate the growth of ovarian cancer) and circulating tumor DNA (ctDNA, which is bits of cancer DNA that can be observed on a blood test) were collected from patients. CT scans were also found and characteristics of the tumor were obtained throughout the CT scans.

Where disease spread in the initial stage was investigated within omental and pelvic/ovarian regions. Omental deposits showed more of a response compared to pelvic disease when it came to neoadjuvant (presurgical) therapy. Before and after therapy responses, tumor mutations and CA-125 had correlation to the overall disease burden, according to the press release.

Analyzation of CT scans showed that six patient subgroups, classified by biological and clinical characteristics became indicators of therapy responses. The efficiency of the model was shown throughout the independent patient sample shown within the study.

"From a clinical perspective, the proposed framework addresses the unmet need to early identify patients unlikely to respond to neoadjuvant therapy and may be directed to immediate surgical intervention," Sala emphasized. "The tool could be applied to stratify the risk of each individual patient in future clinical research...

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Artificial Intelligence May Predict Ovarian Cancer Therapy Outcomes - Curetoday.com

In the rapidly evolving landscape of technology, the fusion of startups and artificial intelligence (AI) has emerged as a beacon of innovation, reshaping industries and redefining the boundaries of what is possible. This dynamic duo is not just a trend but a transformative force, with startups leveraging AI to solve complex problems, enhance efficiency, and create unprecedented value; but it is not without challenges.

The world of technology is witnessing a remarkable era where artificial intelligence has become the cornerstone of innovation.

Amidst this technological renaissance, startups play a crucial role, acting as the crucibles where the raw potential of AI is refined into groundbreaking applications.

These nimble entities, characterized by their innovative spirit, flexibility, and willingness to try anything, are exploring AIs capabilities to attack the status quo by offer solutions that were once discounted as science fiction.

Today you can:

All thanks to the power of AI and emergence of integrating technologies such as mixed reality and the metaverse.

But why are Startups where all of this magic is happening?

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The Synergy of Startups and Artificial Intelligence: | by Dr Richard Matthews - Chief AI Officer RHEM Labs | Jan, 2024 - Medium

Failure to disclose that content was created using artificial intelligence could incur a financial penalty.

Other states have made efforts in recent years to regulate AI election content, with mixed results. Michigan, Minnesota, and Washington state all passed legislation last year to address the issue. But proposals to require disclosure have failed elsewhere, including Indiana, Illinois, and New York according to the National Conference of State Legislatures.

Those are the kinds of things that, when done in proximity to an election, can upend what people want to do in that election, how they vote if they vote, and that is a threat to democracy, said Titone. Shes not just worried about local actors, but that foreign adversaries might take advantage of this technology to create disinformation and try to influence U.S. elections.

However, Titone noted that legislation can only do so much to limit how much-manipulated content is created and distributed. And because any restrictions could potentially butt up against the First Amendment, lawmakers will have to be careful with how the bill is crafted.

Separately, Secretary Griswold is also pushing for a new law to add penalties for anyone who acts as a fake elector in future presidential elections. Some states have prosecuted individuals who submitted certificates naming themselves to the Electoral College based on false claims that former President Donald Trump won the 2020 election.

We want to make sure that it's very clear that if someone tries to do this, they will be facing major penalties, said Griswold.

Democratic Rep. Lorena Garcia of Adams County said she decided to sponsor the false electors bill because she wants to protect the fundamental safeguards of democracy.

We know that Trump's camp is going to go all out in the 2024 election, and we just want to make sure we set our state up for continued success in safe elections, she said.

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If artificial intelligence is going to get involved in elections, Colorado lawmakers want voters to know - Colorado Public Radio

Meta Platforms (META 0.24%) will have more GPU power than almost any company in the world by the end of 2024, and the company plans to make most of its AI models open source. This is a powerful strategy that could destroy value for even the biggest competitors in the industry, as Travis Hoium covers in this video.

*Stock prices used were end-of-day prices of Jan. 23, 2024. The video was published on Jan. 23, 2024.

Randi Zuckerberg, a former director of market development and spokeswoman for Facebook and sister to Meta Platforms CEO Mark Zuckerberg, is a member of The Motley Fool's board of directors. John Mackey, former CEO of Whole Foods Market, an Amazon subsidiary, is a member of The Motley Fool's board of directors. Suzanne Frey, an executive at Alphabet, is a member of The Motley Fool's board of directors. Travis Hoium has positions in Alphabet and Snap. The Motley Fool has positions in and recommends Alphabet, Amazon, Meta Platforms, Microsoft, Nvidia, and Oracle. The Motley Fool has a disclosure policy. Travis Hoium is an affiliate of The Motley Fool and may be compensated for promoting its services. If you choose to subscribe through their link they will earn some extra money that supports their channel. Their opinions remain their own and are unaffected by The Motley Fool.

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Why Mark Zuckerberg Is the Power Player in Artificial Intelligence - The Motley Fool

The artificial intelligence boom has generated many winners like these three stocks

Artificial intelligence (AI) can increase global productivity and help businesses generate more revenue. Those two outcomes and others have captivated investors who seek to beat the market.

Its hard to find an industry that performed as well as AI last year. It may also be challenging to find a sector that can keep up with artificial intelligence stocks in 2024. These stocks wont go parabolic and will have good years and bad years.

However, many of the catalysts that fueled 2023s rally are still in play this year. Its possible for these three AI stocks to soar higher as they capitalize on the artificial intelligence boom.

Source: sdx15 / Shutterstock.com

Nvidia(NASDAQ:NVDA) put investors on notice last year as artificial intelligence caused revenue to surge.Quadruple-digit year-over-year net income growthmade the valuation easier to justify.

Even now, it can be argued that Nvidia is still an undervalued stock. The companys continued growth, business opportunities, 28 forward P/E ratio, and 0.56 PEG ratio form the foundation for this argument.

This company has been one of the best performers in the stock market. Shares are up by 241% over the past year and have gained 1,328% over the past five years. The company has even notched a 19% year-to-date gain. Most indexes have eked out low-single-digit gains this year, if that.

The firm is in a class of its own and has the potential to become the worlds most valuable company. It has grown the most out of the top artificial intelligence players and leads by a wide margin.

Source: The Art of Pics / Shutterstock.com

If Nvidia wants to become the worlds most valuable publicly traded company, it will have to contend with heavyweights:Microsoft(NASDAQ:MSFT) andApple(NASDAQ:AAPL). The two stocks have been jockeying for the top spot with Microsoft having a slight edge at the time of writing.

A 70% gain over the past year and a 268% gain over the past five years make Microsoft stock look appealing for long-term investors. The companys artificial intelligence initiatives can fuel more gains and reward investors who accumulate shares.

Microsofts Azure has anAI platformthat helps developers build apps at enterprise scale. The company has built-in tools to help developers create more effective AI and construct AI workflows.

The company also benefits from the rise of AI through its investment in OpenAI and Microsoft Copilot. Copilot is a new feature that has been built into Microsoft Office Products to increase productivity. The firm is a leading AI stock that continues to deliver double-digit year-over-year revenue and earnings growth.

Source: Benny Marty / Shutterstock.com

Alphabet(NASDAQ:GOOG, NASDAQ:GOOGL) is well-known for its search engine. Google is the worlds most popular website with its own YouTube right behind it. These platforms rely on artificial intelligence to provide consumers with relevant search results. YouTube also recommends videos similar to the one the viewer is currently watching to increase the amount of time people spend on the website.

Attention is money for any company, and Alphabet has demonstrated that it can keep attention for several hours in a given day. While ad revenue is still growing, the company is diversifying into other areas, such as cloud computing, to achieve higher growth rates.

Google Cloud offers severalAI and machine learning productsto help people use generative AI, gather data, and perform other tasks. Alphabet is also at the forefront ofquantum computingthrough AI which can become the next megatrend. Quantum computing is still in its early innings, but artificial intelligence is heating up right now.

Alphabet stock gives you exposure to those sectors, the companys vast advertising business, and other business segments.

On this date of publication, Marc Guberti held long positions in NVDA and MSFT. The opinions expressed in this article are those of the writer, subject to theInvestorPlace.comPublishing Guidelines.

Marc Guberti is a finance freelance writer at InvestorPlace.com who hosts the Breakthrough Success Podcast. He has contributed to several publications, including the U.S. News & World Report, Benzinga, and Joy Wallet.

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3 Stocks Capitalizing on the Artificial Intelligence Boom - InvestorPlace

AMSTERDAM Stellantis N.V. announced today the acquisition of the artificial intelligence framework, machine learning models and intellectual property rights and patents of CloudMade, a developer of smart and innovative big data-driven automotive solutions.

The acquisition as an asset deal will support the mid-term development of STLA SmartCockpit and reinforces Stellantis software strategy outlined in Dare Forward 2030.

The AI-powered framework created by CloudMade, with integrated graphical interfaces, is the industry-leading cloud and software development kit for collecting and analyzing automotive data sets and has been the reference point to transform the in-car and mobility user experience throughout the past decade.

The acquisition of CloudMades pioneering AI capabilities will accelerate our development journey on STLA SmartCockpit and help us deliver our Dare Forward 2030 goals, said Yves Bonnefont,Stellantis Chief Software Officer. Thanks to this adaptable technology and leveraging our growing connected car parc, we will create intelligent mobility solutions faster and with more flexibility, to delight our customers with in-vehicle and mobile experience personalization.

As part of the acquisition, 44 engineers and software developers from CloudMade, dedicated to the development of AI technology, will be joining Stellantis.

CloudMadeis extremely pleased with this transaction, said Jim Brown, founder and CTO of CloudMade. The team is excited to deepen their working relationship withStellantis to bring new features to the vehicles cockpit.

CloudMades framework architecture allows to maximize data value using three learning approaches: personalized learning, which predicts an individuals behavior in a particular context; fleet learning, using sensor data across devices to detect and share real world features; cohort learning, combining real world data with data from clustered groups of people distinguished by attributes.

CloudMades software technology will support Stellantis strategy to develop intelligent mobility products and enhance the overall customer experience with personalized features that will make their drive safer, their life easier and their trip exciting.

Services and products will include:

Through this acquisition, Stellantis will also be able to develop end-to-end and fully owned navigation features; enhance data privacy, since the data for training the models will be managed internally, reducing risks of possible exposure; and introduce development kits for making custom models for its software developers.

About Stellantis

Stellantis N.V. (NYSE: STLA / Euronext Milan: STLAM / Euronext Paris: STLAP) is one of the worlds leading automakers aiming to provide clean, safe and affordable freedom of mobility to all. Its best known for its unique portfolio of iconic and innovative brands including Abarth, Alfa Romeo, Chrysler, Citron, Dodge, DS Automobiles, Fiat, Jeep, Lancia, Maserati, Opel, Peugeot, Ram, Vauxhall, Free2move and Leasys. Stellantis is executing its Dare Forward 2030, a bold strategic plan that paves the way to achieve the ambitious target of becoming a carbon net zero mobility tech company by 2038, while creating added value for all stakeholders. For more information, visit http://www.stellantis.com

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Stellantis to Enhance Personalized Mobility Experience with Acquisition of CloudMade's Artificial Intelligence ... - Stellantis

Bina48, the central figure of the documentary Love Machina, is among the most terrifying film characters of the year. A disembodied head resembling a middle-aged Black woman and powered by artificial intelligence, Bina48 combines a realistic face, dead emotionless eyes, jerky and mechanical head movements, and speech that resembles a voicemail chatbot more than a living being to create an uncanny valley nightmare. But to basically everyone on screen, Bina48 is a dream, a sign of a world where to quote the motto of her makers at the Terasem Movement Life is purposeful. Death is optional. God is technological. Love is essential.

Whether Love Machina agrees with its subjects views about Bina48, and the larger ongoing debates about the ethics of artificial intelligence, is a bit of a mystery even by the time its credits roll. In taking us into the story of the AI, director Peter Sillen opts for a fairly neutral approach that acknowledges some counterarguments and complications, enough that the film cant be called full-throttle AI propaganda. But the failure to take a strong stance either way makes for a boringly ambivalent film, one that fails to either enchant with promises of the future or terrify with warnings of whats to come.

As the title suggests, Love Machina fashions itself as a story of a marriage, though it doesnt dig particularly deeply into the relationship between its central characters. Bina48 is modeled after Bina Rothblatt, the wife of massively successful lawyer, satellite technology and biotechnology entrepreneur, and SiriusXM founder Martine Rothblatt. Married for over 40 years, Martine and Bina are almost oppressively in love (they even give themselves their own ship name, MarBina), and their pet project the Terasem Movement is intended as a gigantic tribute to their bond. Based on (the Rothblatts interpretations of) beloved sci-fi author Octavia Butlers works, the Terasem Movement seeks to find a way to upload peoples consciousness into artificial intelligence, to cheat death and live forever. Bina is essentially the guinea pig for the organizations efforts, her robot doppelganger powered by an algorithm based on her mind file, a virtual upload of the real womans personality and experiences based on a series of rigorous interviews.

The Terasem Movement and its goals raise a lot of obvious philosophical questions, but Love Machina doesnt try to ask them. The Rothblatts and the majority of the people interviewed in the film among them Terasem managing director Bruce Duncan, the Hanson Robotics engineers that developed Bina48, two of the couples children, and a gaggle of assorted artificial intelligence experts dont reveal any negative or contradictory feelings about the rise of AI or undercut the Rothblatts unwavering vision for the future in any way. Fascinating discussions about deaths role in human life, the nature of human consciousness, and the religious implications of living forever beg to be had about Terasems work, but the film doesnt want to start them.

The movie does tip its toes into the most uncomfortable element of the Bina48 story, the fact that a replica of a Black woman was created by a team of (seemingly) all-white people. Love Machina doesnt ignore it, including scenes where the team that created her discuss the difficulties that came from sculpting Black skin after previously making exclusively white male robots. The only person willing to probe deeper into the subject that we see in the film is Stephanie Dinkins, a professor and artist known for her series of videos in which she converses with Bina48. Dinkins, a Black woman who specializes in art exploring artificial intelligence, isnt necessarily anti-AI, but she reveals her discomfort with Bina48 as a representative of a Black woman, one whose code falls short of grasping the social context of her race. Its easily the most interesting discussion that the film has, but one that gets siloed off into a short section rather than meaningfully incorporated into the films discussions of AI at large.

Thats not the only angle of the film that goes unexamined. Frequently, Love Machina comes across as two films in one: a film about a marriage, and a film about the broader world of artificial intelligence. Rather than complement each other, both stories only flatten when paired together. The refusal to take a particularly strong approach to the question of artificial intelligence means theres very little interesting discussion about the topic to be had, and the film runs out of anything to say about Bina48 and its role in the advancement of AI very early on. In the final few minutes of the film, Sillen loses any semblance of focus and takes detours into the worlds of cryogenics and conversations with AI experts unrelated to Bina48, with little sense of how to meaningfully incorporate them into the broader film. All this is presented in a competent but thoroughly visual and editing style, that a few slightly creepy shots of Bina48 aside is content to just float from talking head to coverage without a real sense of style.

The Rothblatts story, presented via archival photos and video interviews done during the process of creating Binas mind file, is a potentially richer text that gets similarly diluted. For a film ostensibly about marriage, the recounting of their love story is painfully surface-level; you never actually know what draws the two into their passionate relationship. There are interesting threads about Martines gender transition and life as a prominent and powerful trans woman and the interracial nature of their family that the movie approaches timidly and fluffily, never adding dimension beyond the basic facts.

Late in the film, its revealed that part of the couples obsession with preventing death comes from the horrifying experience of witnessing one of their children go through a bout of childhood illness. Because the documentary doesnt tell us much about any of these people, the revelation doesnt particularly invite an emotional response. Like a lot of AI art, Love Machina is too fixated on technological advancement to leave any room for real, interesting human feelings.

Love Machina premiered at the 2024 Sundance Film Festival. It is currently seeking distribution.

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'Love Machina' Review: Artificial Intelligence Doc Fails to Ask the Interesting Questions - IndieWire

Artificial Intelligence (AI) is not just revolutionizing technology; its also opening up new avenues for making money. This article delves into the ways individuals can leverage AI to create income streams, offering insights and expert advice for those looking to capitalize on this rapidly evolving field.

Explore the diverse ways in which AI can be harnessed for generating income. From automation to data analysis, understand the broad spectrum of opportunities that AI presents for individuals seeking financial success.

Delve into specific niches within the AI landscape that offer lucrative income potential. Whether its AI-driven content creation, virtual assistance, or machine learning applications, discover where your skills and interests align.

Learn about the essential skills required to make money with AI. From programming languages to understanding algorithms, discover how individuals can prepare themselves for the evolving demands of the AI-driven job market.

Explore the world of freelancing in AI. Discover platforms and opportunities where individuals can offer their AI expertise to businesses and individuals in need of AI-driven solutions.

Uncover the potential of developing AI products. From AI-powered applications to specialized software, learn how to create and market products that leverage the capabilities of artificial intelligence.

Explore the role of AI in content creation. From automated writing tools to AI-generated visuals, discover how individuals can monetize their AI-enhanced content creation skills in various industries.

Understand the demand for AI solutions in the business world. Explore how individuals can create tailored AI solutions to address specific business needs, offering consulting or development services.

Delve into the world of AI competitions. Platforms like Kaggle offer opportunities for individuals to showcase their AI prowess and win cash prizes, providing a unique avenue for making money with AI skills.

Uncover the potential of creating educational content around AI. Whether through online courses, tutorials, or webinars, individuals can monetize their AI knowledge by sharing it with aspiring learners.

Q: Do I need a technical background to make money with AI? While a technical background is beneficial, there are opportunities for individuals with varying levels of expertise. Non-technical roles, such as AI consulting or content creation, also exist.

Q: Can I make money with AI without a formal education in the field? Yes, practical experience and skills often carry significant weight in the AI industry. Self-learning, certifications, and real-world projects can contribute to your success.

Q: Are there ethical considerations in AI income opportunities? Yes, ethical considerations are crucial in AI. Individuals should be mindful of the responsible use of AI and stay updated on ethical guidelines in the industry.

Q: How can I stay updated on the latest developments in AI? Engage with online communities, attend webinars, and follow reputable sources in the AI field. Continuous learning is key to staying informed and competitive.

Q: What are the potential risks of monetizing AI knowledge? Potential risks include ethical concerns, ensuring the security of AI solutions, and staying compliant with relevant regulations. Understanding and mitigating these risks is essential for success.

Q: Can I make money with AI as a side hustle? Yes, many AI opportunities can be pursued as a side hustle. Freelancing, content creation, and participating in competitions are examples of flexible AI income avenues.

Embark on the exciting journey of making money with AI, leveraging its transformative capabilities to create income streams. With strategic insights and a commitment to continuous learning, individuals can position themselves for success in the dynamic and lucrative world of AI-driven income.

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Making Money with AI: Unleashing the Potential of Artificial Intelligence - Medium

By Chris Stokel-WalkerFeatures correspondent

A start-up is developing a news service presented by anchors created by artificial intelligence. Will it upend decades of parasocial relationships between television audiences and the people they watch on screen?

The footage wouldn't look out of place on many of the world's news channels.

For 22 minutes, a variety of polished news anchors stand in front of the camera and run down the day's news in a video posted on social media . But none of them are real. Instead, the anchors are generated by artificial intelligence (AI).

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The video is produced by Los Angeles-based Channel 1, a start-up created by entrepreneurs Adam Mosam and Scott Zabielski, who plan to roll out AI-generated news on a streaming TV channel later this year. "There seemed to be a very interesting opportunity to level up the user experience of news," says Mosam, by using AI to tailor content to individuals.

AI technology can also help translate scripts and interviews from one language to another capabilities that Channel 1 demonstrated in a promotional video, which was shared in December.

Channel 1 is the latest demonstration of AI-powered news presenters around the world. In Kuwait, an AI persona by the name of Fedha ran through the headlines for Kuwait News. Hermes presented the news in May 2023 for Greek state broadcaster ERT. South Korean broadcaster SBShanded over the duties of news presenting to Zae-In, an AI-generated deepfake, for five months this year. There are others in India and Taiwan, too all created by AI.

But there's one key question still to be answered: will viewers trust news delivered by AI, rather than humans?

Trust in the humans presenting the news has dropped to an all-time low, according to a survey by public opinion polling firm Ipsos. Just 42% of people in the UK trust TV newsreaders, down 16 percentage points in a year. The scepticism around news presenters as independent arbiters of truth is an unusual modern phenomenon, with many choosing to get their news instead from individual creators or influencers.

Those social media stars leverage a connection with their audience called parasocial influence. First coined in the 1950s by academics at the University of Chicago, parasocial relationships were defined as the belief that viewers of nightly news programmes of the time had that the anchor behind the desk was talking through the camera directly to them. News presenters became more than just journalists telling you the news; they were friends, welcomed into your living rooms night after night.

Social media influencers have co-opted that same direct to camera format and perceived personal connection to great success. "It's interesting how the 'parasocial' label has evolved from describing the affinity that individuals might feel with remote newscasters to something way broader," says Christine H Tran, who studies digital platforms and labour at the University of Toronto. "You can be in a parasocial relationship with a reporter or news Twitch streamer," she says, referring to the livestreaming video service. "But you can also apparently be in a parasocial relationship with a YouTuber, a singer, and an Instagram power couple."

But whether AI can replicate the personal connection is less certain. "You'll never have the same connection with an AI that you do with another human being," admits Mosam. However, he argues that people are no longer looking for impartiality. "We're not doing this because we think a robot does a better job than a human that's ridiculous."

The idea of journalists not reading the news isn't all that unusual, even if the idea that they're computer-generated is. "When I started in journalism, you had actors reading the news," says Nic Newman, senior research associate at the Reuters Institute for the Study of Journalism at the University of Oxford, and a former editor at the BBC. "People were kind of fine with that."

The fact that journalists haven't always read the news means that this trial could well succeed with limitations, reckons Newman. It'll only be useful for short news bulletins, but he's less certain that viewers will embrace a parasocial relationship with an AI anchor. "For delivering news programmes, I think the humanity is going to remain really important," he says.

It's an unknown that Tran is also uncertain about. "Will AI personalities inspire the same parasociality if their broadcasts are accurately labelled as 'AI content' and the viewers know there's no personal life outside the screen?" they ask. "That depends on if the platforms hosting AI presenters will be expected to label their content as AI like some platforms such as Instagram have considered moving towards."

Channel 1 and NewsGPT , which claims to be the world's first news channel generated entirely by AI, may have another question to answer: is it possible to totally remove the human from the loop?

At present, Channel 1 has nearly a dozen staff members working on checking AI-generated scripts and selecting stories that ought to be covered. Mosan says there's a 13-step process that Channel 1 goes through for every story before it is aired to ensure some of the issues around generative AI don't make it onto air. These include hallucination, where AI tools make up content, which is obviously a no-no in journalism. The company behind it is looking to hire an editor-in-chief early next year.

Being able to actually find newsworthy events and report on them is another element that AI may struggle with, agree Mosan and Newman. The Channel 1 test episode relied heavily on stories unearthed and footage filmed by human journalists. "Without those sources, if they get cut off, I don't really see how they can do it," says Newman. "If that raw material is not there, then the AI has absolutely nothing to work on."

Mosan believes that there are some elements of the reporting process that can be carried out by AI, but others that can't. "You'll never be able to gather intelligence person-to-person, and interview person-to-person, effectively," he says. "But I could fly a drone and analyse what I'm looking at." Newsgathering solely by AI, without humans in the loop, isn't in Channel 1's current set of plans.

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TV channels are using AI-generated presenters to read the news. The question is, will we trust them? - BBC.com

AI stock picks, courtesy of an AI trained to keep an eye on current trends.

Source: shutterstock.com/Victor Runov

With the steady rise of artificial intelligence, we asked Grok AI for its thoughts on the future of the market. Grok AI, or just Grok, provides a new take on the original ChatGPT format of large language modeling. We then asked it to help identify the top artificial intelligence stocks.

Founded by Elon Musk in March of 2023, xAI aims to integrate the Grok chatbot with X, formerly Twitter. Groks take on AI chatting features more wit and humor than the competition while claiming to seek only truth. With these defining features, Grok provides more up-to-date and pertinent information with the ability to evaluate current events.

This might make it the best AI to ask about the stock market. Through its ability to search the web for news and data, Groks conclusions differ from the standard chatbot. So, how do its stock picks measure up? These three AI stock picks by Grok AI provide some details to consider when using AI to research stocks.

Source: Below the Sky / Shutterstock.com

Nvidia (NASDAQ:NVDA) makes the computers responsible for training AI, so no wonder Grok considers them a good pick. While other AI companies specialize in optimizing software for training their chatbots, Nvidia controls the whole process.

By designing the most efficient graphics processing units (GPUs) on the market, Nvidia maximizes the amount of math its machines perform. Through using GPUs, Nvidias AI training software completes thousands of calculations per second in parallel. This results in blazing-fast speeds for training the chatbot to interpret data and respond with information.

With this unique advantage, Nvidia rapidly transforms its AI applications to respond to industry trends. Groks developers even use Nvidia GPUs to train the bot, which speaks volumes about the critical role of the technology. A lack of serious competition in the GPU space and stellar performance have made Nvidia a strong buy option. It also helps that its one of the AI stock picks by Grok AI.

Source: The Art of Pics / Shutterstock.com

Another solid pick by Grok, Microsofts (NASDAQ:MSFT) position in the AI race comes from its ubiquitous software. Almost every tech user in the world interacts with a Microsoft application in some form or another.

Furthermore, Microsoft now integrates AI in nearly every live service they develop. When a company researching AI has access to this level of data, it results in rapid product development. Add on the fact that Microsofts value continues increasing and this stock continues to be a strong buy. Microsofts investments in OpenAI and ChatGPT also put the company in a diversified position when it comes to research.

Its focus on pioneering new chatbot technologies makes it a direct competitor to Musks Grok project. This makes Grok seem even more trustworthy, as it openly recommends the stock of one of its competing models. Though Microsofts Copilot AI may not be the stuff of headlines yet, its projects show promise.

Source: Tada Images / Shutterstock.com

The last, but certainly not least of AI stock picks by Grok AI is Amazon (NASDAQ:AMZN). While investors focus on Amazons endless retail selection and shipping speeds, the company has an AI ace up its sleeve. By leveraging its Amazon Web Services suites, Amazon possesses endless business data to train AI for practical applications.

Since machine learning serves as the focus of Amazons AI projects, the company currently enables corporations to become more efficient. This unique approach to AI services and Amazons high potential stock make for a strong buy position. With this third pick, Groks preferences for stocks reflect an AI that focuses on strong historical performance and ideal positions.

These types of stocks serve as a benchmark for their industry and tend towards stability. Interestingly enough, an AI programmed to tap into current events and seek truth seems genuinely risk averse. If you are looking for high-value artificial intelligence stocks, start here.

On the date of publication, Viktor Zarevdid not have (either directly or indirectly) any positions in the securities mentioned in this article.The opinions expressed in this article are those of the writer, subject to the InvestorPlace.comPublishing Guidelines.

Viktor Zarev is a scientist, researcher, and writer specializing in explaining the complex world of technology stocks through dedication to accuracy and understanding.

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The 3 Most Promising Artificial Intelligence Stocks in 2024, According to Grok AI - InvestorPlace

From misinformation and invisible cyber attacks, to irresponsible AI that could cause events involving multiple deaths, expert futurists have forecast how rapid technology changes may shape our world by 2040.

As the pace of computer technology advances surges ahead, and systems become increasingly interlinked, it is vital to know how these fast technology advances could impact the world in order to take steps to prevent the worst outcomes.

Using a Delphi study, a well known technique for forecasting, a team of cyber security researchers led by academics from Lancaster University interviewed 12 experts in the future of technologies.

The experts, ranged from chief technology officers in businesses, consultant futurists and a technology journalist to academic researchers. They were asked how particular technologies may develop and change our world over the next 15 years by 2040, what risks they might pose, and how to address the challenges that may arise.

Most of the experts forecasted exponential growth in Artificial Intelligence (AI) over the next 15 years, and many also expressed concern that corners could be cut in the development of safe AI. They felt that this corner cutting could be driven by nation states seeking competitive advantage. Several of the experts even considered it possible that poorly implemented AI could lead to incidents involving many deaths, although other experts disagreed with this view.

Dr Charles Weir, Lecturer at Lancaster Universitys School of Computing and Communications and lead researcher of the study, said: Technology advances have brought, and will continue to bring, great benefits. We also know there are risks around some of these technologies, including AI, and where their development may goeveryones been discussing thembut the possible magnitude of some of the risks forecast by some of the experts was staggering.

But by forecasting what potential risks lie just beyond the horizon we can take steps to avoid major problems.

Another significant concern held by most of the experts involved in the study was that technology advances will make it easier for misinformation to spread. This has the potential to make it harder for people to tell the difference between truth and fiction with ramifications for democracies.

Dr Weir said: We are already seeing misinformation on social media networks, and used by some nation states. The experts are forecasting that advances in technologies will make it much easier for people and bad actors to continue spreading misleading material by 2040.

Other technologies were forecast to not have as big as impact by 2040, including quantum computing which experts see as having impacts over a much longer timeframe, and Blockchain which was dismissed by most of the experts as being a source of major change.

The experts forecast that:

By 2040, competition between nation states and big tech companies will lead to corners being cut in the development of safe AI

Quantum computing will have limited impact by 2040

By 2040 there will be ownership of public web assets. These will be identified and traded through digital tokens

By 2040 it will be harder to distinguish truth from fiction because widely accessible AI can massively generate doubtful content

By 2040 there will be less ability to distinguish accidents from criminal incidents due to the decentralised nature and complexity of systems

The forecasters also offered some suggested solutions to help mitigate against some of the concerns raised. Their suggestions included governments introducing AI purchasing safety principles, new laws to regulate AI safety. In addition, universities could be vital by introducing courses combining technical skills and legislation.

These forecasts will help policy makers and technology professionals make strategic decisions around developing and deploying novel computing technologies. They are outlined in the paper Interlinked Computing in 2040: Safety, Truth, Ownership and Accountability which has been published by the peer-reviewed journalIEEE Computer.

The papers authors are: Charles Weir and Anna Dyson of Lancaster University; Olamide Jogunola and Katie Paxton-Fear of Manchester Metropolitan University; and Louise Dennis of Manchester University.

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Misinformation And Irresponsible AI: Experts Forecast How Technology May Shape Our Near Future - Eurasia Review

In this video, I will talk about three AI semiconductor companies that will greatly benefit from the AI revolution. These companies aren't talked about as much as Nvidia, AMD, or Intel, but they play an increasingly important role in the industry.

*Stock prices used were from the trading day of Jan. 22, 2024. The video was published on Jan. 23, 2024.

Neil Rozenbaum has positions in Intel. The Motley Fool has positions in and recommends Advanced Micro Devices, Nvidia, and Qualcomm. The Motley Fool recommends Intel and Super Micro Computer and recommends the following options: long January 2023 $57.50 calls on Intel, long January 2025 $45 calls on Intel, and short February 2024 $47 calls on Intel. The Motley Fool has a disclosure policy. Neil is an affiliate of The Motley Fool and may be compensated for promoting its services. If you choose to subscribe through his link, he will earn some extra money that supports his channel. His opinions remain his own and are unaffected by The Motley Fool.

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3 Magnificent Artificial Intelligence (AI) Semiconductor Stocks to Buy in 2024 - The Motley Fool