Daily Archives: January 2, 2024

Artificial intelligence (AI) has been around for decades, but this year was a breakout for the spooky technology, with OpenAI's ChatGPT creating accessible, practical AI for the masses. AI, however, has a checkered history, and today's technology was preceded by a short track record of failed experiments.

For the most part, innovations in AI seem poised to improve things like medical diagnostics and scientific discovery. One AI model can, for example, detect whether you're at high risk of developing lung cancer by analyzing an X-ray scan. During COVID-19, scientists also built an algorithm that could diagnose the virus by listening to subtle differences in the sound of people's coughs. AI has also been used to design quantum physics experiments beyond what humans have conceived.

But not all the innovations are so benign. From killer drones to AI that threatens humanity's future, here are some of the scariest AI breakthroughs likely to come in 2024.

We don't know why exactly OpenAI CEO Sam Altman was dismissed and reinstated in late 2023. But amid corporate chaos at OpenAI, rumors swirled of an advanced technology that could threaten the future of humanity. That OpenAI system, called Q* (pronounced Q-star) may embody the potentially groundbreaking realization of artificial general intelligence (AGI), Reuters reported. Little is known about this mysterious system, but should reports be true, it could kick AI's capabilities up several notches.

Related: AI is transforming every aspect of science. Here's how.

AGI is a hypothetical tipping point, also known as the "Singularity," in which AI becomes smarter than humans. Current generations of AI still lag in areas in which humans excel, such as context-based reasoning and genuine creativity. Most, if not all, AI-generated content is just regurgitating, in some way, the data used to train it.

But AGI could potentially perform particular jobs better than most people, scientists have said. It could also be weaponized and used, for example, to create enhanced pathogens, launch massive cyber attacks, or orchestrate mass manipulation.

The idea of AGI has long been confined to science fiction, and many scientists believe we'll never reach this point. For OpenAI to have reached this tipping point already would certainly be a shock but not beyond the realm of possibility. We know, for example, that Sam Altman was already laying the groundwork for AGI in February 2023, outlining OpenAI's approach to AGI in a blog post. We also know experts are beginning to predict an imminent breakthrough, including Nvidia's CEO Jensen Huang, who said in November that AGI is in reach within the next five years, Barrons reported. Could 2024 be the breakout year for AGI? Only time will tell.

One of the most pressing cyber threats is that of deepfakes entirely fabricated images or videos of people that might misrepresent them, incriminate them or bully them. AI deepfake technology hasn't yet been good enough to be a significant threat, but that might be about to change.

AI can now generate real-time deepfakes live video feeds, in other words and it is now becoming so good at generating human faces that people can no longer tell the difference between what's real or fake. Another study, published in the journal Psychological Science on Nov. 13, unearthed the phenomenon of "hyperrealism," in which AI-generated content is more likely to be perceived as "real" than actually real content.

This would make it practically impossible for people to distinguish fact from fiction with the naked eye. Although tools could help people detect deepfakes, these aren't in the mainstream yet. Intel, for example, has built a real-time deepfake detector that works by using AI to analyze blood flow. But FakeCatcher, as it's known, has produced mixed results, according to the BBC.

As generative AI matures, one scary possibility is that people could deploy deepfakes to attempt to swing elections. The Financial Times (FT) reported, for example, that Bangladesh is bracing itself for an election in January that will be disrupted by deepfakes. As the U.S. gears up for a presidential election in November 2024, there's a possibility that AI and deepfakes could shift the outcome of this critical vote. UC Berkeley is monitoring AI usage in campaigning, for example, and NBC News also reported that many states lack the laws or tools to handle any surge in AI-generated disinformation.

Governments around the world are increasingly incorporating AI into tools for warfare. The U.S. government announced on Nov. 22 that 47 states had endorsed a declaration on the responsible use of AI in the military first launched at The Hague in February. Why was such a declaration needed? Because "irresponsible" use is a real and terrifying prospect. We've seen, for example, AI drones allegedly hunting down soldiers in Libya with no human input.

AI can recognize patterns, self-learn, make predictions or generate recommendations in military contexts, and an AI arms race is already underway. In 2024, it's likely we'll not only see AI used in weapons systems but also in logistics and decision support systems, as well as research and development. In 2022, for instance, AI generated 40,000 novel, hypothetical chemical weapons. Various branches of the U.S. military have ordered drones that can perform target recognition and battle tracking better than humans. Israel, too, used AI to rapidly identify targets at least 50 times faster than humans can in the latest Israel-Hamas war, according to NPR.

But one of the most feared development areas is that of lethal autonomous weapon systems (LAWS) or killer robots. Several leading scientists and technologists have warned against killer robots, including Stephen Hawking in 2015 and Elon Musk in 2017, but the technology hasn't yet materialized on a mass scale.

That said, some worrying developments suggest this year might be a breakout for killer robots. For instance, in Ukraine, Russia allegedly deployed the Zala KYB-UAV drone, which could recognize and attack targets without human intervention, according to a report from The Bulletin of the Atomic Scientists. Australia, too, has developed Ghost Shark an autonomous submarine system that is set to be produced "at scale", according to Australian Financial Review. The amount countries around the world are spending on AI is also an indicator with China raising AI expenditure from a combined $11.6 million in 2010 to $141 million by 2019, according to Datenna, Reuters reported. This is because, the publication added, China is locked in a race with the U.S. to deploy LAWS. Combined, these developments suggest we're entering a new dawn of AI warfare.

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3 scary breakthroughs AI will make in 2024 - Livescience.com

Introduction

Artificial intelligence (AI) has been around for decades, but new advancements have brought the technology to the fore. Experts say its rise could mirror previous technological revolutions, adding billions of dollars worth of productivity to the global economy while introducing a slew of new risks that could upend the global geopolitical order and the nature of society itself.

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Managing these risks will be essential, and a global debate over AI governance is raging as major powers such as the United States, China, and European Union (EU) take increasingly divergent approaches toward regulating the technology. Meanwhile, AIs development and deployment continues to proceed at an exponential rate.

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While there is no single definition, artificial intelligence generally refers to the ability of computers to perform tasks traditionally associated with human capabilities. The terms origins trace back to the 1950s, when Stanford University computer scientist John McCarthy used the term artificial intelligence to describe the science and engineering of making intelligent machines. For McCarthy, the standard for intelligence was the ability to solve problems in a constantly changing environment.

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Since 2022, the public availability of so-called generative AI tools, such as the chatbot ChatGPT, has raised the technologys profile. Generative AI models draw from massive amounts of training data to generate statistically probable outcomes in response to specific prompts. Tools powered by such models generate humanlike text, images, audio, and other content.

Another commonly referenced form of AI, known as artificial general intelligence (AGI), or strong AI, refers to systems that would learn and apply knowledge like humans do. However, these systems do not yet exist and experts disagree on what exactly they would entail.

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Researchers have been studying AI for eighty years, with mathematicians Alan Turing and John von Neumann considered to be among the disciplines founding fathers. In the decades since they taught rudimentary computers binary code, software companies have used AI to power tools such as chess-playing computers and online language translators.

In the countries that invest the most in AI, development has historically relied on public funding. In China, AI research is predominantly funded by the government, while the United States for decades drew on research by the Defense Advanced Research Projects Agency (DARPA) and other federal agencies. In recent years, U.S. AI development has largely shifted to the private sector, which has poured hundreds of billions of dollars into the effort.

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In 2022, U.S. President Joe Biden signed the CHIPS and Science Act, which refocuses U.S. government spending on technology research and development. The legislation directs $280 billion in federal spending toward semiconductors, the advanced hardware capable of supporting the massive processing and data-storage capabilities that AI requires. In January 2023, ChatGPT became the fastest-growing consumer application of all time.

The arrival of AI marks a Big Bang moment, the beginning of a world-changing technological revolution that will remake politics, economies, and societies, Eurasia Group President Ian Bremmer and Inflection AI CEO Mustafa Suleyman write for Foreign Affairs.

Companies and organizations across the world are already implementing AI tools into their offerings. Driverless-car manufacturers such as Tesla have been using AI for years, as have investment banks that rely on algorithmic models to conduct some trading operations, and technology companies that use algorithms to deliver targeted advertising. But after the arrival of ChatGPT, even businesses that are less technology-oriented began turning to generative AI tools to automate systems such as those for customer service. One-third of firms around the world that were surveyed by consultancy McKinsey in April 2023 claimed to be using AI in some capacity.

Widespread adoption of AI could speed up technological innovation across the board. Already, the semiconductor industry has boomed; Nvidia, the U.S.-based company that makes the majority of all AI chips, saw its stock more than triple in 2023to a total valuation of more than $1 trillionamid skyrocketing global demand for semiconductors.

Many experts foresee a massive boon to the global economy as the AI industry grows, with global gross domestic product (GDP) predicted to increase by an additional $7 trillion annually within the next decade. Economies that refuse to adopt AI are going to be left behind, CFR expert Sebastian Mallaby said on an episode of the Why It Matters podcast. Everything from strategies to contain climate change, to medical challenges, to making something like nuclear fusion work, almost any cognitive challenge you can think of is going to become more soluble thanks to artificial intelligence.

Like many other large-scale technological changes in history, AI could breed a trade-off between increased productivity and job loss. But unlike previous breakthroughs, which predominantly eliminated lower-skill jobs, generative AI could put white-collar jobs at riskand perhaps supplant jobs across many industries more quickly than ever before. One quarter of jobs around the world are at a high risk of being replaced by AI automation, according to the Organization for Economic Cooperation and Development (OECD). These jobs tend to rely on tasks that generative AI could perform at a similar level of quality as a human worker, such as information gathering and data analysis, a Pew Research Center study found. Workers with high-exposure to replacement by AI include accountants, web developers, marketing professionals, and technical writers.

The rise of generative AI has also raised concerns over inequality, as the most high-skilled jobs appear to be the safest from disruptions related to the technology, according to OECD. But other analysis suggests that low-skilled workers could benefit by drawing on AI tools to boost productivity: a 2023 study by researchers at the Massachusetts Institute of Technology (MIT) and Stanford University found that less-experienced call center operators doubled the productivity gains of their more-experienced colleagues after both groups began using AI.

AIs relationship with the environment heralds both peril and promise. While some experts argue that generative AI could catalyze breakthroughs in the fight against climate change, others have raised alarms about the technologys massive carbon footprint. Its enormous processing power requires energy-intensive data centers; these systems already produce greenhouse gas emissions equivalent to those from the aviation industry, and AIs energy consumption is only expected to rise with future advancements.

AI advocates contend that developers can use renewable energy to mitigate some of these emissions. Tech firms including Apple, Google, and Meta run their data centers using self-produced renewable energy, and they also buy so-called carbon credits to offset emissions from any energy use that relies on fossil fuels.

There are also hopes that AI can help reduce emissions in other industries by enhancing research on renewables and using advanced data analysis to optimize energy efficiency. In addition, AI can improve climate adaptation measures. Scientists in Mozambique, for example, are using the technology to better predict flooding patterns, bolstering early warning systems for impending disasters.

Many experts have framed AI development as a struggle for technological primacy between the United States and China. The winner of that competition, they say, will gain both economic and geopolitical advantage. So far, U.S. policymakers seem to have operated with this framework in mind. In 2022, Biden banned exports of the most powerful semiconductors to China and encouraged U.S. allies to do the same, citing national security concerns. One year later, Biden proposed an outright ban on several streams of U.S. investment into Chinas AI sector, and the Department of Commerce announced a raft of new restrictions aimed at curbing Chinese breakthroughs in artificial intelligence. Most experts believe the United States has outpaced China in AI development to date, but that China will quickly close the gap.

AI could also have a more direct impact on U.S. national security: the Department of Defense expects the technology to transform the very character of war by empowering autonomous weapons and improving strategic analysis. (Some experts have pushed for a ban on autonomous lethal weapons.) In Ukraines war against Russia, Kyiv is deploying autonomously operated AI-powered drones, marking the first time a major conflict has involved such technology. Warring parties could also soon rely on AI systems to accelerate battlefield decisions or to automatically attack enemy infrastructure. Some experts fear these capabilities could raise the possibility of nuclear weapons use.

Furthermore, AI could heighten the twin threats of disinformation and propaganda, issues that are gaining particular relevance as the world approaches a year in which more people are set to vote than ever before: more than seventy countries, representing half the global population, will hold national elections in 2024. Generative AI tools are making deep fakes easier to create, and the technology is already appearing in electoral campaigns across the globe. Experts also cite the possibility that bad actors could use AI to create sophisticated phishing attempts that are tailored to a targets interests to gain access to election systems. (Historically, phishing has been a way into these systems for would-be election hackers; Russia used the method to interfere in the 2016 U.S. election, according to the Department of Justice.)

Together, these risks could lead to a nihilism about the existence of objective truth that threatens democracy, said Jessica Brandt, policy director for the Brookings Institutions Artificial Intelligence and Emerging Technology Initiative, on the podcast The Presidents Inbox.

Some experts say that its not yet accurate to call AI intelligent, as it doesnt involve human-level reasoning. They argue that it doesnt create new knowledge, but instead aggregates existing information and presents it in a digestible way.

But that could change. OpenAI, the company behind ChatGPT, was founded as a nonprofit dedicated to ensuring that AGI benefits humanity as a whole, and its cofounder, Sam Altman, has argued that it is not possible or desirable to stop the development of AGI; in 2023, Google DeepMind CEO Demis Hassabis said AGI could arrive within five years. Some experts, including CFR Senior Fellow Sebastian Mallaby, contend that AI has already surpassed human-level intelligence on some tasks. In 2020, DeepMind used AI to solve protein folding, widely considered until then to be one of the most complex, unresolved biological mysteries.

Many AI experts seem to think so. In May 2023, hundreds of AI leaders, including the CEOs of Anthropic, Google DeepMind, and OpenAI, signed a one-sentence letter that read, Mitigating the risk of extinction from AI should be a global priority alongside other societal-scale risks such as pandemics and nuclear war.

One popular theory for how extinction could happen posits that a directive to optimize a certain task could lead a super-intelligent AI to accomplish its goal by diverting resources away from something humans need to live. For example, an AI tasked with reducing the amount of harmful algae in the oceans could suck oxygen out of the atmosphere, leading humans to asphyxiate. While many AI researchers see this theory as alarmist, others say the example accurately illustrates the risk that powerful AI systems could cause vast, unintentional harm in the course of carrying out their directives.

Skeptics of this debate argue that focusing on such far-off existential risks obfuscates more immediate threats, such as authoritarian surveillance or biased data sets. Governments and companies around the world are expanding facial-recognition technology, and some analysts worry that Beijing in particular is using AI to supercharge repression. Another risk occurs when AI training data contains elements that are over- or underrepresented; tools trained on such data can produce skewed outcomes. This can exacerbate discrimination against marginalized groups, such as when AI-powered tenant-screening algorithms trained on biased data disproportionately deny housing to people of color. Generative AI tools can also facilitate chaotic public discoursehallucinating false information that chatbots present as true, or polluting search engines with dubious AI-generated results.

Almost all policymakers, civil society leaders, academics, independent experts, and industry leaders agree that AI should be governed, but they are not on the same page about how. Internationally, governments are taking different approaches.

The United States escalated its focus on governing AI in 2023. The Biden administration followed up its 2022 AI Bill of Rights by announcing a pledge from fifteen leading technology companies to voluntarily adopt shared standards [PDF] for AI safety, including by offering their frontier models for government review. In October 2023, Biden issued an expansive executive order aimed at producing a unified framework for safe AI use across the executive branch. And one month later, a bipartisan group of senators proposed legislation to govern the technology.

EU lawmakers are moving ahead with legislation that will introduce transparency requirements and restrict AI use for surveillance purposes. However, some EU leaders have expressed concerns that the law could hinder European innovation, raising questions of how it will be enforced. Meanwhile, in China, the ruling Chinese Communist Party has rolled out regulations that include antidiscrimination requirements as well as the mandate that AI reflect Socialist core values.

Some governments have sought to collaborate on regulating AI at the international level. At the Group of Seven (G7) summit in May 2023, the bloc launched the so-called Hiroshima Process to develop a common standard on AI governance. In October 2023, the United Nations formed an AI Advisory Boardwhich includes both U.S. and Chinese representativesto coordinate global AI governance. The following month, twenty-eight governments attended the first ever AI Safety Summit, held in the United Kingdom. Delegates, including envoys from the United States and China, signed a joint declaration warning of AIs potential to cause catastrophic harm and resolving to work together to ensure human-centric, trustworthy and responsible AI. China has also announced its own AI global governance effort for countries in its Belt and Road Initiative.

AIs complexity makes it unlikely that the technology could be governed by any one set of principles, CFR Senior Fellow Kat Duffy says. Proposals run the gamut of policy options with many levels of potential oversight, from total self-regulation to various types of public-policy guardrails.

Some analysts acknowledge that AIs risks have destabilizing consequences but argue that the technologys development should proceed. They say that regulators should place limits on compute, or computing power, which has increased by five billion times over the past decade, allowing models to incorporate more of their training data in response to human prompts. Others say governance should focus on immediate concerns such as improving the publics AI literacy and creating ethical AI systems that would include protections against discrimination, misinformation, and surveillance.

Some experts have called for limits on open-source models, which can increase access to the technology, including for bad actors. Many national security experts and leading AI companies are in favor of such rules. However, some observers warn that extensive restrictions could reduce competition and innovation by allowing the largest AI companies to entrench their power within a costly industry. Meanwhile, there are proposals for a global framework for governing AIs military uses; one such approach would be modeled after the International Atomic Energy Agency, which governs nuclear technology.

The U.S.-China relationship looms large over AI governance: as Beijing pursues a national strategy aimed at making China the global leader in AI theories, technologies, and applications by 2030, policymakers in Washington are struggling with how to place guardrails around AI development without undermining the United States technological edge.

Meanwhile, AI technology is rapidly advancing. Computing power has doubled every 3.4 months since 2012, and AI scientists expect models to contain one hundred times more compute by 2025.

In the absence of robust global governance, companies that control AI development are now exercising power typically reserved for nation-states, ushering in a technopolar world order, Bremmer and Suleyman write. They argue that these companies have become themselves geopolitical actors, and thus they need to be involved in the design of any global rules.

AIs transformative potential means the stakes are high. We have a chance to fix huge problems, Mallaby says. With proper safeguards in place, he says, AI systems can catalyze scientific discoveries that cure deadly diseases, ward off the worst effects of climate change, and inaugurate an era of global economic prosperity. Im realistic that there are significant risks, but Im hopeful that smart people of goodwill can help to manage them.

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What Is Artificial Intelligence (AI)? - Council on Foreign Relations

The science and technology of building computers and systems that are capable of reasoning, learning, making decisions, and solving problems tasks that typically require human intellect is known as artificial intelligence (AI). The availability of vast volumes of data, the creation of potent computer hardware and software, and the invention of novel algorithms and models have all contributed to AIs recent rapid advancement. Artificial Intelligence has been implemented in a number of fields and sectors, including industry, banking, education, and entertainment. But one of the most widespread and significant uses of AI is in our daily lives, where it may facilitate our work and personal lives, increase our comfort and convenience, and improve our overall experience and happiness. This post will provide you with further information on artificial intelligence (AI), including its workings, advantages and disadvantages, and instances of its application in real-world situations both now and in the future.

Artificial Intelligence operates through the use of algorithms and models that, without explicit programming or instruction, may learn from data and gradually improve their performance. Two categories of AI exist: narrow and general. Using AI for certain, well-defined tasks, like chess play, facial recognition, or language translation, is known as narrow AI. General AI refers to the application of AI to any activity that a person can perform, including the comprehension of natural language, logical reasoning, and emotional expression. While narrow AI is currently a reality and affects our daily lives, general AI remains a theoretical and unattainable objective. Additionally, AI may be separated into two categories: sub-symbolic and symbolic. Symbolic AI is the use of AI to represent and process knowledge and information by manipulating symbols and rules, such as those found in logic, mathematics, or linguistics. Sub-symbolic AI is modeling and simulating intricate and dynamic events and systems utilizing AI that can learn from data and patterns, such as neural networks, genetic algorithms, or fuzzy logic.

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6. AI in Everyday Life How Artificial Intelligence is Impacting Society - Medium

The worldwide relevance of artificial intelligence, known by its acronym AI, is evident in front of us through numbers. And these numbers only show us that 2023 is the real inflection point in the growth trajectory of AI. It is the year from which AI will take off at a never-seen-before exponential speed.

Some estimates suggestthat the worldwide AI market will grow at a CAGR of more than 37% between 2023 and 2030. To elaborate as to how impactful AI's contribution in the future could be,

PricewaterhouseCoopers estimates suggest that AI will contribute nearly US$16 trillion to the global economy by 2030, which would be more than the current output of India and China combined. It will positively impact labor productivity and help achieve enhanced levels of personalization, save time, and improve quality.

It will benefit all parts of the globe. However, some regions will gain more than others. China may receive a 26% rise in GDP in 2030, followed by North America (14.5% boost), Southern Europe (11.5% boost), and the developed parts of Asia (10.4% boost).

This magnificent rise of AI stems from and thrives on the innovations that this field has achieved over the past few years. We will look at some such breakout innovations in AI in the following segments.

ChatGPT by OpenAI has probably been the most well-known AI product of 2023. It has helped fuel the imagination of ordinary people and freed the perception of AI from being thought of as something to be used only in technology-intensive workspaces and application scenarios.

OpenAI, the entity behind developing ChatGPT, wants Artificial General Intelligence or AGI a paradigm of AI systems that will be smarter than humans to benefit humanity. ChatGPT is only the beginning of that journey.

At its core, ChatGPT is a form of generative AI that can serve many purposes in a human-like fashion. As a chatbot, it leverages natural language processing techniques to come up with human-like conversational responses. It can respond to questions, compose elaborate written content, and offer images, text, or videos in response to text-based user prompts, which are similar to queries we input in a search engine.

The acronym GPT stands for Generative Pre-Trained Transformer since the application has been trained with reinforcement learning through human feedback.

According tothe latest available data, ChatGPT has more than 180 million users, while the website generated 1.7 billion visits in October 2023.

While Netflix took around three and a half years to reach one million subscribers and Instagram had to wait nearly 2.5 months to acquire the same traffic, ChatGPT acquired 1 million subscribers within its first five days.

According to thelatest available informationpublished in the last week of December 2023, Open AI was in preliminary discussions for a fresh funding round that could take the valuation of the company to US$100 billion, making it the second-most valuable US startup behind SpaceX. The company was also in talks with G42 for a billion-dollar investment in its Chip Venture.

While speaking toTIME Magazineabout AI's potential, Sam Altman, the CEO of OpenAI, said, I think AGI will be the most powerful technology humanity has yet invented. He specifically stressed AI's capabilities in democratizing access to information globally.

While ChatGPT has helped AI gain massive traction, its revolutionary impacts have been realized by the medical field with greater intensity in 2023. AI has found its use in disease detection and diagnosis, personalized disease treatment, medical imaging, efficient clinical trials, drug development, and more such application areas.

It has helped make patient care a more informed practice with reduced scope for errors. It has also helped reduce the costs of care by introducing customized virtual health assistance and preventing the process through which a healthcare system interacts with a patient.

In mid-September 2023, a group of medical AI researcherspublished about RETFound. They defined it as the:

Foundation model for retinal images that learns generalizable representations from unlabelled retinal images and provides a basis for label-efficient model adaptation in several applications.

Trained on 1.6 million unlabeled retinal images, the RETFound can diagnose and predict eye diseases and systemic disorders such as heart failure and myocardial infarction.

In October 2023,researchers in the United Kingdomfound that an AI algorithm could do better than a biopsy at grading the aggressiveness of the sarcomas.

Sarcomas is a rare form of cancer that grows in our connective tissues, including fat, muscle, and nerves. The technology could grade the aggressiveness of the tumor accurately up to 82% of the time, a significant improvement to biopsies that were accurate 44% of the time.

The tool also successfully differentiated between leiomyosarcoma and liposarcoma in 84% of the cases, while radiologists could correctly ascertain in 65% of cases.

Christina Messiosu, the consultant radiologist at the Royal Marsden and professor in imaging for personalized oncology at the ICR, said:

In the future, this approach may help characterize other types of cancer, not just retroperitoneal sarcoma. Our novel approach used features specific to this disease, but by refining the algorithm, this technology could one day improve the outcomes of thousands of patients each year.

One of the tech giants involved in Healthcare AI is IBM. Its WatsonX Assistant AI healthcare chatbots can help skilled medical professionals efficiently focus on the core problem while helping patients on the other side of the spectrum to get a fast and stress-free healthcare experience. It was in 2023 that IBM announced the WatsonX platform.

At a functional level, the platform can help partners train, tune, and distribute models with generative AI and machine learning capabilities. In short, it can manage the life cycle of foundational models that serve as the basis of generative AI.

For thethird quarter of 2023, IBM registered a revenue of US$14.8 billion, up 3.5 percent at constant currency. The gross profit margin was 54.4 percent (GAAP), up 1.7 percent.

Overall, by the middle of 2023,692 AI deviceshad received approval from the United States Food and Drug Administration for clinical use, a 33% increase from 2022.

The achievements of AI were so significant in 2023 that Matt Mohebbi, the head of AI and research at Brightside Health in New York, not only termed the year a blockbuster' but went on to say that the:

Clinicians who embrace these technologies will very likely replace the clinicians who don't.

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Another industry space where AI scored significantly well in 2023 was the automotive industry. The automotive industry leveraged a range of AI capabilities to improve their safety standards, efficiency, and autonomous driving standards. These capabilities included machine learning, natural language processing, and computer vision.

One of the most revolutionizing impacts of AI in the automotive industry was in the form of Advanced Driver Assistance Systems or ADAS. ADAS features thrived on AI. AI algorithms and sensors helped monitor the vehicle's surroundings and identify potential dangers so that drivers could move and park their cars with minimized risk of collisions.

AI-powered predictive analytics also helped in vehicle maintenance. The AI algorithms could identify patterns and anomalies to predict potential failure or breakdowns.

AI also helped sellers and dealers to offer a better customer experience with personalized driving features and voice assistants that could adjust the vehicle temperature, inform the driver about fuel or gas levels, make calls, and even change radio stations.

Apart from improving in-vehicle safety and customer experience, AI also benefited the automotive manufacturing industry. It helped consolidate the supply chain and bring more efficiency to it by introducing robotics and automation. It also helped in quality control and defect detection.

The automotive design and development sectors leveraged AI's capabilities, such as generative design and optimization features, simulation and virtual testing, and rapid prototyping and iterative development.

One of the major players in deploying AI in the automotive industry has been Tesla. Tesla has not only kept innovating but also managed to achieve scale with those innovations.

By the end of 2023, the AI and Robotics portfolio of Tesla included Tesla Bot, FSD Chip, Dojo Chip and Dojo System, Neural Networks, Autonomy Algorithms, Code Foundations, Evaluation Infrastructure, and much more.

The company, for instance, has built AI inference chips to run its self-driving software. It has built AI training chips to power its Dojo System, from the silicon firmware interfaces to the high-level software APIs meant to control it.

According to Ashok Elluswamy, the director of Autopilot Software at Tesla:

Tesla cars running the FSD (Full Self Driving) software which currently numbers about 400,000 customers will be able to make more intelligent self-driving decisions with the hardware upgrades, which will improve the company's overall AI capabilities.

Currently, the company has an AI system that can gather real-time visual data from eight cameras to produce a 3D output to identify and help make decisions on overcoming obstacles, controlling and optimizing vehicle motion, effective driving through lanes and roads, responding to traffic lights, and more.

The company, at present, banks on its AI system powered by 14,000 GPUs in its data center that can tap into 30 petabytes of video cache. Soon, it will grow to 200 petabytes, an enormous support of processing power and storage.

Its innovations and the capability to be in sync with the latest technologies have helped Tesla see consistent growth in revenue earned over the last three consecutive years. In FY 2022, FY 2021, and FY 2020,Tesla earned revenuesof more than US$67 billion, 44 billion, and 24 billion, respectively.

While companies like Open AI, Tesla, IBM, and many more such companies and research institutions have broadened the horizon for AI in a big way, the road ahead looks even more promising and exciting.

Artificial Intelligence will revolutionize many fields. It is better to say that there won't be any area of application shortly that would not leverage the benefits of AI. Research and development efforts towards AI have increased significantly over the past few years.

According to theArtificial Intelligence Index Report 2023, published by Stanford University's Human-Centered Artificial Intelligence (HAI) Center, the number of AI research collaborations between the United States and China has increased nearly four times since 2010. The total number of AI publications has more than doubled during the same period.

Increased volume of research will open up many new frontiers for AI to succeed shortly.

In mid-December 2023, Google made it public that they were making the next generation of Imagen.

Shortly, Imagen will alter the field of visual representation radically by helping to create emblems, letter marks, and abstract logos and also facilitating their overlaying onto products, clothing, business cards, and other surfaces. It will surpass Amazon's Titan Image Generator by rendering text in multiple languages, including Chinese, Hindi, Japanese, Korean, Portuguese, English, and Spanish, with more to come in 2024.

If you want to create images with a text overlay for example, advertising you can do that.

Google Cloud CEO Thomas Kurian said while elaborating on the benefits of the latest version of Imagen

It will expedite the pace and help save costs in many industries, including advertising, designing, printing, packaging, and much more.

Generative AI solutions like ChatGPT have already altered the traditional patterns of disseminating and receiving knowledge. In the future, more changes will come.

The United States Office of Educational Technology published a report in May 2023 titledArtificial Intelligence and the Future of Teaching and Learning. The report said that, shortly, AI would drive more changes in the way we currently offer inputs to these AI solutions, how they process it, and the output they end up providing.

For instance, the current input mechanisms involve:

Now, the edtech AI solutions help display information and tasks, sequence learning activities, and check student work. And in the future, it will assist students and teachers by helping them plan and adapt activities and reveal patterns in student work.

The output that comes now in the form of text, graphics, multimedia, and dashboards will come in the form of conversations, annotations and highlights, suggestions and recommendations, and assistance in organizing and guiding.

More solutions like Gradescopewill come. Adapted by more than 2,600 universities and applied to more than 700 million questions by more than 3.2 million students, Gradescope helps grade all of your assessments, whether online or in class. It has helped more than 140,000 educators so far to get a clear idea of their students' performance.

From advertising and packaging to education, the range of AI is as wide as it can get. And if that is not enough, it is helping address matters as complex as climate change and space exploration.

In the future, industry analysts expect AI to help more intensively in the areas of weather prediction and disaster management. It will help optimize energy consumption and minimize the emission of greenhouse gasses by empowering smart grids and other types of optimized energy consumption algorithms. There is also the notion of AI-powered precision agriculture on the horizon that will improve crop yield, make farming sustainable, and reduce wastage.

In space exploration, companies like SpaceX and Blue Origin are making substantial AI investments so that they can help identify potential xoplants and analyze their suitability for human habitation. Space will become increasingly commercialized in the future, and AI will help shape the nature of that.

With AI occupying more and more of our lives each passing day, ethical considerations on how to leverage this technology are becoming more and more critical. It must not increase the existing inequalities. Rather, it should try to bridge the prevailing gaps to make the world a more equitable space in the future. It must not intrude into our private lives and should be secure, fair, transparent, and unbiased.

Governments, councils of unions, academia, and businesses should all put their energies together to ensure that the future of AI is a safe, reliable, and truly uplifting one.

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2023 Was A Breakout Year for AI - What Can We Expect Looking Forward? - Securities.io

Science fiction sometimes depicts real science science, a saying that rings increasingly true in our technological landscape. The realm of science fiction has long been a canvas for the wildest imaginations of writers and filmmakers, envisaging technologies that seemed light-years away. Yet, many of these fantastical innovations have astonishingly transformed into realities over the past three decades. Mobile phones, once depicted as communicators in Star Trek, have become ubiquitous. The concept of virtual reality, a recurring theme in movies like Tron (1982), has now materialized into a tangible, immersive experience. Similarly, AI assistants, reminiscent of HAL 9000 from 2001: A Space Odyssey (1968), are now an integral part of our daily digital interactions. As we delve into the technological marvels of 2024 and beyond, we find ourselves not just witnessing but living in a world where once-fictional technologies are now cornerstones of our reality. In this article, I want to delve into the most impactful technologies set to redefine industries, economies, and daily life in 2024 and beyond and which movies have already depicted them.

Generative AI is leading a new wave of innovation by creating data-driven content. This is coupled with knowledge graphs that provide a structured representation of data and concepts, enhancing AIs contextual understanding.

Generative AI leverages algorithms like GANs (Generative Adversarial Networks) to produce original content. Knowledge graphs, on the other hand, use nodes and edges to represent and interconnect information, enabling more sophisticated data analysis. The concept of Responsible AI embeds ethical considerations into AI development, ensuring fairness and transparency.

Westworld intricately explores the depth of AI, reflecting the complex ethical dimensions of Generative and Responsible AI. Black Mirror Season 6 Joan is Awful explores how generative AI and quantum computing can be used to create real-time fake realities. It involves creating new, original content based on existing data, and quantum computing, known for its potential to process vast amounts of data at high speeds.

Artificial General Intelligence (AGI) represents the zenith of AI research a machine with the ability to understand, learn, and apply intelligence across a broad spectrum of human capabilities. Unlike narrow AI, which excels in specific tasks, AGI embodies versatile, human-like cognition.

AGI transcends the limitations of task-specific algorithms. It involves the integration of diverse cognitive functions like reasoning, general problem-solving, and abstract thinking, mirroring the human brains versatility. This contrasts with Generative AI, which, while advanced, focuses on creating content within specific parameters, lacking the broader understanding and adaptability inherent to AGI.

The quest for AGI echoes in movies like A.I. Artificial Intelligence (2001) where robots exhibit human-like consciousness and cognitive abilities, encapsulating the profound and complex nature of AGI.

Web 3.0 and its successors represent a paradigm shift in internet usage, emphasizing decentralization, blockchain technology, and token-based economics. This evolution brings a new level of user sovereignty, with data privacy and ownership at its core.

The backbone of Web 3.0 lies in its blockchain infrastructure, enabling immutable data storage and smart contracts. NFTs (Non-Fungible Tokens) are revolutionizing digital ownership, each representing a unique digital asset verifiable via blockchain.

Ready Player One offers a glimpse of a decentralized digital universe, resonating with the principles of Web 3.0 and beyond.

6G is set to succeed 5G, offering exponentially higher data speeds, lower latency, and massive network capacity. It is the cornerstone of the Internet of Everything, connecting a myriad of devices and services.

6G will leverage advanced technologies like sub-terahertz (THz) frequency bands and sophisticated MIMO (Multiple Input Multiple Output) antenna systems. These advancements will facilitate technologies such as holographic communications, ultra-precise location sensing, and enhanced mobile broadband.

Movies like Blade Runner and The Fifth Element depict advanced urban mobility, akin to what 6G technology could enable with flying cars and drone-based services.

Quantum computing represents a quantum leap in computational power, harnessing the principles of quantum mechanics to process information in fundamentally new ways.

Quantum computers use quantum bits or qubits, which, unlike classical bits, can exist in multiple states simultaneously (superposition). This allows for parallel processing on a scale unachievable by classical computers. Quantum computing holds immense potential in areas like quantum cryptography, complex system modeling, and optimization problems.

Star Treks portrayal of parallel universes echoes the multi-state quantum mechanics principle. Eagle Eye , and Gods Eye in Fast and the Furious depict the power of supercomputers.

Multimodal computing integrates various input methods like voice, gesture, and touch, enhancing human-computer interaction. This is converging with the industrial metaverse, a digital twin of the physical world, creating immersive, interconnected digital environments.

Multimodal systems utilize advanced AI and ML algorithms for natural language processing, computer vision, and haptic feedback, providing a seamless user experience.

In Iron Man, Tony Starks computer system, J.A.R.V.I.S., is a prime example of multimodal interaction, responding to voice, gesture, and visual input, closely mirroring the concept of multimodal computing.

Model compression techniques optimize AI models for performance and efficiency, enabling their integration into compact devices like the Humane Pin, a wearable AI device.

Model compression involves techniques like pruning, quantization, and knowledge distillation to reduce the size of neural network models without significantly compromising their performance. This enables the deployment of advanced AI in edge devices with limited computational resources.

The wearable tech in Minority Report foreshadows the integration of AI in everyday gadgets, akin to the Humane Pin.

Neuromorphic computing involves creating computer chips that mimic the human brains neural structure, leading to more energy-efficient and powerful computing systems.

This technology uses analog circuits to replicate neuro-biological architectures present in the nervous system, enhancing machine learning and AI capabilities. It holds promise in areas like sensory processing, brain modeling, and autonomous decision-making.

Ex Machina showcases advanced AI, echoing the principles of neuromorphic computing in creating machines with human-like cognitive abilities.

Autonomous vehicles and ADAS are transforming transportation, utilizing advanced technologies for safer and more efficient driving with minimal human intervention.

These systems use a combination of sensors, cameras, radar, and AI to navigate, detect obstacles, and make decisions. This technology ranges from basic assistance systems like automatic braking to fully autonomous vehicles that handle all driving tasks.

The self-driving cars in I, Robot and Total Recall offer a glimpse into the future of autonomous vehicles.

BCIs link the human brain to external devices, enabling direct communication and control through neural activity.

These interfaces involve translating neuronal information into commands capable of controlling software or hardware, offering potential applications in medicine, gaming, and communication.

The Matrix showcases a form of BCI where characters download skills and information directly to their brains.

The lines between technology and imagination continue to blur, propelling us toward an exciting and uncharted future. These technologies, once the domain of cinematic imagination, are now tangible realities or within our grasp. In the words of Arthur C. Clarke, Any sufficiently advanced technology is indistinguishable from magic.

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2024 Tech Predictions: From Sci-Fi Fantasy to Reality - Exploring Cinematic Tech Prophecies - Medium

The major LLM players, as well as third-party developers using LLM APIs, will get us to genuinely AGI-ish levels during 2024.

Depending on your definition of AGI, artificial general intelligence.

Multimodal (visual etc) AI will be part of it, but the NLU (natural language understanding) provided by LLMs will be and always was the key to AGI.

NLU is not just about content creation. NLU is actually bottled intelligence. When you solve NLU, you get intelligence as part of that. How else can the LLM write sensibly if its not intelligent? Even during 2023 the most interesting use of LLMs was in intelligent decision making, not content generation.

To be useful, AGI need not be sentient, super intelligent or even necessarily multi-modal.

Thats why its close.

Early AGI will be quite simple.

The key step required by a minimal AGI is simply resilient independence in not entirely controlled environments, whether cyber or real world.

It neednt pass every test either. Engineering is iterative. Even though the aim of AGI is in principle complete independence, well initially be happy to see AGIs that can solve some of the problems of unconstrained environments.

AGI does indeed need long and short term memory and goal creation and task facilitation skills.

None of these capabilities are anything as difficult to add to an LLM as the 70 year grand challenge that LLMs already solved, namely shockingly good NLU.

The addition of short and long term memory is being attacked from multiple angles: increased prompt sizes and RAG (retrieval augmented generation) for example.

And LLMs, with the right app flow, are ready for decision making roles important for resilience or for goal creation and task facilitation.

What well see during 2024 is a plethora of AGI-ish apps operating in the cyber world in text and multimodal form factors.

And then in bots and androids including Teslas Optimus project from mid-2024.

Most of these early attempts will be prescriptively designed, iterative ad hoc solutions to mimic human-like behaviour.

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AGI predictions for 2024. The major LLM players, as well as | by Paul Pallaghy, PhD | Dec, 2023 - Medium

Photo by ALEXANDRE LALLEMAND on Unsplash

The year 2023 marked a significant turning point for artificial intelligence (AI), and as we step into 2024, the world anticipates even more frightening advancements. From the potential emergence of Artificial General Intelligence (AGI) to the escalating threat of realistic deepfakes and the integration of AI in military applications, the upcoming year holds promises and perils that demand our attention.

The mysterious Q* (pronounced Q-star) from OpenAI is rumored to be at the forefront of a breakthrough in AGI. AGI represents a theoretical point where AI surpasses human intelligence, leading to the Singularity. While AGI could revolutionize various fields, its potential misuse, including the creation of enhanced pathogens or cyber attacks, poses a grave threat to humanity. Despite skepticism, experts like Nvidias CEO suggest AGI might be within reach by 2024, raising questions about its ethical implications.

Deepfake technology has evolved, reaching a point where real-time, indistinguishable video feeds are generated. The emergence of hyperrealism poses a significant challenge, making it nearly impossible for the naked eye to differentiate between authentic and AI-generated content. With potential consequences ranging from misinformation to election interference, the impending integration of deepfakes into our daily lives requires vigilance and technological countermeasures.

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10 Scary Breakthroughs AI Will Make in 2024 | by AI News | Dec, 2023 - Medium

Midjourney The Nature of AI Cognition

AIs current state is a far cry from human-like cognition. Todays AI systems, even the most advanced ones, operate based on algorithms and data patterns. They lack the intrinsic qualities of human thought, such as consciousness, emotion, and understanding. While AI can mimic certain aspects of human intelligence, like learning or problem-solving, it does so in a fundamentally different way.

Artificial General Intelligence (AGI) represents the idea of a machine with the ability to understand, learn, and apply intelligence as broadly as a human. Despite significant strides in AI research, AGI remains a theoretical concept. Current AI systems, known as Narrow AI, are highly specialized and operate within a limited context.

One of the significant limitations of AI is its inability to genuinely understand human emotions and contextual nuances. While there are AI systems designed to recognize facial expressions or analyze speech patterns, their understanding of emotions is based on data and predefined algorithms, lacking the depth and subtlety of human emotional intelligence.

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Top 5 Myths About AI Debunked. Unraveling the Truth: Separating AI | by Michiel Meire | Dec, 2023 - Medium