In the Global Race to Lead on Artificial Intelligence, America Must Win – uschamber.com

Across the country, artificial intelligence is powering machines and computers to help us solve problems and work more efficiently. Its assisting scientists to develop vaccines and treat patients more effectively, securing our nations networks and critical infrastructure against cyberattacks, alerting customers of bank fraud and expanding financial opportunities for underserved communities through access to credit, and much more. AI is rapidly changing how businesses operateand is foundational to a thriving 21st-century economy. By 2030, 70% of businessesglobally expect to use AI. Around the world, AI is estimated to boost global GDP by 14% over the same period, accounting for nearly $16 trillion of economic output.

From basic needs, such as food security and supply chain resiliency, to ensuring our nations competitive advantage through research and development and the intellectual property rights that underpin it, AI will shape the new economic era. Its no wonder that, according to a poll conducted by the U.S. Chamber Technology Engagement Center (C_TEC) 80% of Americans feel its vital for the U.S. to lead the world in AI. The reality before us is as simple as it is stark: whoever leads in the advancement of AI will lead the global economy.

To that end, were seeing allies and strategic competitors pursue AI leadership. Earlier this year, Russia and China announced they would work cooperatively to develop AI. Of course, China is already investing heavily in this space in parallel to engaging in IP theft and cyber espionage to steal American innovation. At the same time, our friends and partners in Europe are looking to write regulations around data and AI, some of which could disadvantage U.S. businesses if not carefully constructed. Nations worldwide are racing ahead and we must not fall behind.

We must get the policy environment right to enable American innovators to lead the AI revolution. With government and industry working together, we will ensure that becomes a reality. We will compete against nations in research and development, create an environment where AI is used responsibly, respect personal liberties, and ensure our workforce is prepared for an AI-driven future. The work of this Commission is a critical next step in the U.S. Chambers leadership on this issue, building on the AI principles we released in 2019.

Recently, the U.S. Chamber Artificial Intelligence Commission on Competition, Inclusion, and Innovation wrapped its final field hearing. The U.S. Chamber formed this Commission in January to better understand how our nation can lead the world in adopting AI technologies and enact sound regulations to harness its potential.

Co-chaired by former Congressman John Delaney and former Congressman Mike Ferguson, the Commission has held public hearings in Austin, Cleveland, Palo Alto, London, and Washington, DC, bringing together thought leaders, researchers, and experts in industry, academia, and civil society. Here is what the Commission found during those public hearings:

As AI grows increasingly ubiquitous in our everyday lives and crucial to our nations economic growth, these issues are inextricably linked. This Fall, we look forward to the Commissions final recommendations to help guide policymakers toward durable, bipartisan AI policy solutions. The U.S.Chamber is committed to ensuring our recommendations produce actions, and those actions produce results.

Executive Vice President, Center for Capital Markets Competitiveness (CCMC), U.S. Chamber of Commerce, Executive Vice President, Center for Technology Engagement (C_TEC), U.S. Chamber of Commerce, Executive Vice President, Global Innovation Policy Center (GIPC), U.S. Chamber of Commerce, Senior Advisor to the President and CEO, U.S. Chamber of Commerce

Tom Quaadman develops and executes strategic policies to implement a global corporate financial reporting system, address ongoing attempts of minority shareholder abuse of the proxy system, communicate the benefits of efficient American capital markets, and promote an innovation economy and the long-term interests of all investors.

Read more

Continued here:
In the Global Race to Lead on Artificial Intelligence, America Must Win - uschamber.com

New initiative pushes for artificial intelligence innovation in newsrooms – International Journalists’ Network

Technology in journalism is always evolving. From smartphone journalism, to reporting the news on Twitter and TikTok, to data journalism, modern reporters rely on new technology to make their jobs easier and their stories more impactful and engaging.

Today, large newsrooms are introducing a new technology, artificial intelligence (AI), to their work. Smaller newsrooms are interested in this tool too, even if they cant implement it yet. Some predictions say that 90% of news will be written by AI by 2025 in fact, youve likely already read a sports story or election rundown that was at least partially authored by an AI.

AI can be generally understood as any technology that simulates human intelligence: extracting patterns from data, predicting future events and/or adapting performance based on past mistakes. Not all AI is futuristic: transcription software, for example, uses AI to recognize and generate words from an audio file.

AI isnt meant to replace the work of journalists. Instead, AI takes over repetitive, simple or data-intensive work so that human journalists can focus on stories that require creative insight, multifaceted analysis and good judgment.

In 2019, Polis, the London School of Economics media think tank, and the Google News Initiative partnered to create the JournalismAI initiative to promote the use of artificial intelligence among journalists. The JournalismAI Fellowship Program began this year, with the goal of innovating new tools that assist the work of journalists.

To learn more about how AI is influencing journalism, I interviewed initiative manager & team lead Mattia Peretti and fellowship program manager Lakshmi Sivadas on the fellowship, the initiative and what JournalismAIs projects mean for the future of newsrooms.

The fellowship originates from a series of Collab Challenges that the JournalismAI staff held between 2020 and 2021. According to Peretti, the Collab Challenges arose organically, with no application process or formal organization for people interested in participating. Plenty of useful AI-based projects were completed during the challenges, many of which are still available online. The following year the process was formalized and altered to create the fellowship.

While the Journalism AI initiative is focused on educating journalists unfamiliar with artificial intelligence, the fellowship program goes a step further by fostering the skills of journalists already using AI technology in the newsroom.

What we can do for them, through the fellowship, is connect them with a global network of people at the same level, said Peretti. By getting them to collaborate with each other, we can help them accelerate the adoption and implementation of AI, and show everyone in our community what's possible.

Forty-six different journalists were selected for the program. In total, 16 countries across six continents are represented in the cohort. With problems already emerging with AI developing racial and gender biases and racially profiling people of color, the JournalismAI staff heavily encouraged diversity when accepting fellows.

Our idea was that if we bring in people who are representative of major populations around the world, they could recognize the kind of biases that exist in current data sets, said Sivadas. Then, in the systems that they are building or developing right now with the fellowship, they would be able to figure out where bias enters the development process, and mitigate that as well.

The main goal of the fellowship is to create a software incorporating AI to benefit the teams newsrooms and newsrooms globally. Unlike OpenAI or Googles DeepMind, whose research focuses on creating artificial general intelligence software that functions as an independent human brain JournalismAIs projects are all tools that require the input or supervision of human journalists.

Most of these projects aim to assist with one of the three areas in news that the 2019 JournalismAI report outlined: gathering information, producing content or distributing the finished content to an audience.

Each of these areas has exciting potentials for journalism. Newsgathering AI can identify trends and monitor the mention of issues or events, and source information, for example by collecting and citing articles from various news outlets that all discuss the same issue. News production AIs, which work in content creation, can write bullet-pointed articles or reformat stories for different audiences in a fraction of the time it would take a human to do so. Finally, news distribution AIs take input from consumers to make news more impactful: finding likely audiences for an organizations content, tracking readers behavior and personalizing newsflow so readers see what theyre most interested in.

There is not one single journalism student that decided to take this career path because they were dying to sift through PDF documents day after day, said Peretti. That's something machine learning does very well, and I think we should be excited that we can have the support of software doing all these things for us.

Some of the mentors for the teams this year include Ines Montani, co-founder and CEO of the software company Explosion; David Caswell, former BBC News Labs product manager; and various members of the Knight Lab at Northwestern University. These mentors fill needs for fact-checking, advanced technical skill and more.

We didn't prepare a roster of mentors and tell [the fellows], These are your mentors, work with them, because there would have been no point when we didnt know yet what the teams would want to work on. So we tried to find subject matter experts that could help them for the specific case that they are exploring, said Peretti. We start from the needs of our teams.

Ten projects are coming out of the fellowship this year. Among them are Attack Detector, which aims to detect hate speech towards journalists and environmental activists in Spanish and Portuguese, and Parrot, which identifies and measures the spread of state-manufactured media. These two, along with all the other projects, will be showcased at the JournalismAI festival in early December.

Peretti said that all of these projects are made with ethical AI use in mind. None of them are meant to run without human supervision, adding that it would be extremely dangerous to allow for unsupervised use at this time.

The word we use again and again is responsible, said Peretti. I'm encouraged by what I'm seeing in the industry and I want to presume that a little bit of that is due to the work we do. But we need to continue to stress [responsible use of AI] if we really want AI to be a force of good for journalism.

Sivadas believes that AI is becoming more prevalent in global newsrooms, and soon it will be inescapable. She quoted previous 2020 Collab Challenge participant Michala Cancela in saying, You can either choose to be a part of the people who are making decisions about how it's going to be used, or you can sit back and watch it destroy the systems and ethical practices that journalism was built on.

Photo by Umberto on Unsplash.

Original post:
New initiative pushes for artificial intelligence innovation in newsrooms - International Journalists' Network

Insights on the Artificial Intelligence for Drug Discovery and Development Global Market to 2027 – AI Cloud to Create a Streamlined and Automated…

DUBLIN, Aug. 18, 2022 /PRNewswire/ -- The "Global Artificial Intelligence for Drug Discovery and Development Market (2022-2027) by Offering, Application, End User, Technology, Geography, Competitive Analysis and the Impact of Covid-19 with Ansoff Analysis" report has been added to ResearchAndMarkets.com's offering.

The Global Artificial Intelligence for Drug Discovery and Development Market is estimated to be USD 1.22 Bn in 2022 and is expected to reach USD 4.8 Bn by 2027, growing at a CAGR of 31.54%.

Market dynamics are forces that impact the prices and behaviors of the stakeholders. These forces create pricing signals which result from the changes in the supply and demand curves for a given product or service. Forces of Market Dynamics may be related to macro-economic and micro-economic factors.

There are dynamic market forces other than price, demand, and supply. Human emotions can also drive decisions, influence the market, and create price signals. As the market dynamics impact the supply and demand curves, decision-makers aim to determine the best way to use various financial tools to stem various strategies for speeding the growth and reducing the risks.

Company Profiles

The report provides a detailed analysis of the competitors in the market. It covers the financial performance analysis for the publicly listed companies in the market. The report also offers detailed information on the companies' recent development and competitive scenario. Some of the companies covered in this report are Aria Pharmaceuticals Inc, Atomwise Inc., BenevolentAI, BioSymetrics, Cloud Pharmaceuticals, etc.

Countries Studied

Competitive Quadrant

The report includes Competitive Quadrant, a proprietary tool to analyze and evaluate the position of companies based on their Industry Position score and Market Performance score. The tool uses various factors for categorizing the players into four categories. Some of these factors considered for analysis are financial performance over the last 3 years, growth strategies, innovation score, new product launches, investments, growth in market share, etc.

Ansoff Analysis

The report presents a detailed Ansoff matrix analysis for the Global Artificial Intelligence for Drug Discovery and Development Market. Ansoff Matrix, also known as Product/Market Expansion Grid, is a strategic tool used to design strategies for the growth of the company. The matrix can be used to evaluate approaches in four strategies viz. Market Development, Market Penetration, Product Development and Diversification.

The matrix is also used for risk analysis to understand the risk involved with each approach. The analyst analyses the Global Artificial Intelligence for Drug Discovery and Development Market using the Ansoff Matrix to provide the best approaches a company can take to improve its market position. Based on the SWOT analysis conducted on the industry and industry players, the analyst has devised suitable strategies for market growth.

Why buy this report?

Key Topics Covered:

1 Report Description

2 Research Methodology

3 Executive Summary3.1 Introduction3.2 Market Size, Segmentations and Outlook

4 Market Dynamics4.1 Drivers4.1.1 Need for Control Drug Discovery Process and Cost Reduction 4.1.2 Increasing Need to Manage the Large Data Generated During Preclinical Studies4.1.3 Increasing Adoption Across Biopharmaceutical Companies4.2 Restraints4.2.1 Unavailability of Skilled Professionals4.3 Opportunities4.3.1 AI Cloud to Create a Streamlined and Automated Approach in Drug Discovery4.3.2 Increasingly Growing R&D Investments4.4 Challenges4.4.1 Limited Availability of Data Sets

5 Market Analysis5.1 Regulatory Scenario5.2 Porter's Five Forces Analysis5.3 Impact of COVID-195.4 Ansoff Matrix Analysis

6 Global Artificial Intelligence for Drug Discovery and Development Market, By Offering6.1 Introduction6.2 Services6.3 Software

7 Global Artificial Intelligence for Drug Discovery and Development Market, By Application7.1 Introduction7.2 Cardiovascular Disease7.3 Immuno-Oncology7.4 Metabolic Diseases7.5 Neurodegenerative Diseases

8 Global Artificial Intelligence for Drug Discovery and Development Market, By End User8.1 Introduction8.2 Contract Research Organizations8.3 Pharmaceutical & Biotechnology Companies8.4 Research Centers and Academic & Government Institutes

9 Global Artificial Intelligence for Drug Discovery and Development Market, By Technology9.1 Introduction9.2 Machine Learning9.2.1 Deep Learning9.2.2 Supervised Learning9.2.3 Reinforcement Learning9.2.4 Unsupervised Learning9.2.5 Other Machine Learning Technologies9.3 Other Technologies

10 Americas' Artificial Intelligence for Drug Discovery and Development Market10.1 Introduction10.2 Argentina10.3 Brazil10.4 Canada10.5 Chile10.6 Colombia10.7 Mexico10.8 Peru10.9 United States10.10 Rest of Americas

11 Europe's Artificial Intelligence for Drug Discovery and Development Market11.1 Introduction11.2 Austria11.3 Belgium11.4 Denmark11.5 Finland11.6 France11.7 Germany11.8 Italy11.9 Netherlands11.10 Norway11.11 Poland11.12 Russia11.13 Spain11.14 Sweden11.15 Switzerland11.16 United Kingdom11.17 Rest of Europe

12 Middle East and Africa's Artificial Intelligence for Drug Discovery and Development Market12.1 Introduction12.2 Egypt12.3 Israel12.4 Qatar12.5 Saudi Arabia12.6 South Africa12.7 United Arab Emirates12.8 Rest of MEA

13 APAC's Artificial Intelligence for Drug Discovery and Development Market13.1 Introduction13.2 Australia13.3 Bangladesh13.4 China13.5 India13.6 Indonesia13.7 Japan13.8 Malaysia13.9 Philippines13.10 Singapore13.11 South Korea13.12 Sri Lanka13.13 Thailand13.14 Taiwan13.15 Rest of Asia-Pacific

14 Competitive Landscape14.1 Competitive Quadrant14.2 Market Share Analysis14.3 Strategic Initiatives14.3.1 M&A and Investments14.3.2 Partnerships and Collaborations14.3.3 Product Developments and Improvements

15 Company Profiles15.1 Aria Pharmaceuticals Inc15.2 Atomwise Inc15.3 BenevolentAI15.4 BioSymetrics15.5 Cloud Pharmaceuticals15.6 Cyclica15.7 Deep Genomics15.8 Envisagenics15.9 Exscientia15.10 IBM15.11 Insitro15.12 Novartis AG15.13 Nvidia15.14 Owkin Inc15.15 Verge Genomics15.16 XtalPi

16 Appendix

For more information about this report visit https://www.researchandmarkets.com/r/awqyve

Media Contact:

Research and MarketsLaura Wood, Senior Manager[emailprotected]

For E.S.T Office Hours Call +1-917-300-0470For U.S./CAN Toll Free Call +1-800-526-8630For GMT Office Hours Call +353-1-416-8900

U.S. Fax: 646-607-1904Fax (outside U.S.): +353-1-481-1716

Logo: https://mma.prnewswire.com/media/539438/Research_and_Markets_Logo.jpg

SOURCE Research and Markets

Here is the original post:
Insights on the Artificial Intelligence for Drug Discovery and Development Global Market to 2027 - AI Cloud to Create a Streamlined and Automated...

Artificial Intelligence Is All Around Us. So This District Designed Its Own AI Curriculum – Education Week

The description of artificial intelligence in high school may conjure up a science fiction novel where robots stand around chatting at their lockers.

The reality, at Seckinger High School in Gwinnett County, Ga., looks more like this: A social studies teacher pauses a lesson on the spread of cholera in the 19th century to discuss how data scientists use AI tools today to track diseases. A math class full of English-language learners uses machine learning to identify linear and non-linear shapes.

The simplest explanation of this technology is that it trains a machine to do tasks that simulate some of what the human brain can do. That means it can learn to do things like recognize faces and voices (helpful for radiology, security, and more), understand natural language, and even make recommendations. (Think of the algorithm Netflix uses to suggest your next binge-worthy TV show.)

While the Gwinnett County school district, which with more than 177,000 students is among the largest in the country, opened Seckinger high school this month to relieve overcrowding elsewhere, the focus of the school is unique. Seckinger is apparently the only high school in the country dedicated to teaching AI as part of its curriculum, not just as an elective class, according to CSforAll, a nonprofit group dedicated to expanding computer science education in schools across the country.

The district has also expanded the focus on artificial intelligence to three nearby elementary schools and a feeder middle school, creating an AI cluster. Ultimately, Gwinnett aims to expose kids to AI in every subject, as they move from kindergarten to 12th grade. Students who find themselves particularly drawn to the topic will get opportunities to delve even deeper into how artificial intelligence works and the ethical implications of using it.

Through the cluster, Gwinnett plans to do more than just prepare kids for success in a hot corner of the job market: It wants to give them a critical window into how AI is reshaping nearly every aspect of the economy.

Our students need to understand the implications of the technology that they are consuming, and how its being used on them so that they can make informed decisions, said Sallie Holloway, the districts director of artificial intelligence and computer science. (Holloway said shes never spoken to another district leader who had AI in a job title.)

Gwinnett is taking a bold step to help students prepare for the present and the future, said Joseph South, the chief learning officer for the International Society for Technology in Education, a nonprofit group that runs the largest educational technology conference in the country.

We talk like AI is coming, South said. But its actually already here. Its all around us. Theres no part of our society that isnt going to be touched by [AI]. To the extent that its invisible to us, we dont have any power over it. It has power over us. To the extent that we understand it, and even better know how to design it, then we can start to partner with AI, instead of being controlled by AI.

Gwinnett officials didnt have to look far for examples of longstanding industries whose work had evolved to include an AI twist.

An agricultural machinery company headquartered in the county now calls itself a technology company, and utilizes self-driving tractors. An assistant superintendent stopped in at a nearby caf where robots mixed the drinks, and the man behind the counter was an engineer, not a barista.

That drove home to district officials that the kids who graduated our high school who might have gone with traditional trades [in the past] are going to need some more technical AI-driven skills, Holloway said.

Whats more, they see embracing AI as particularly important for a district as diverse as Gwinnett.Its been well-documented that intelligent machines reflect the same biases as the humans programming them. Facial recognition software powered by AI has had trouble picking up darker complexions. AI-driven risk-assessment algorithms used to figure out criminal sentences tend to make harsher predictions about Black defendants than white ones.

Those problems might not be so prevalent, experts say, if more of the engineers behind the technology came from the demographic groups that make up much of Gwinnetts student population.

We serve the students who are most underrepresented in the technology industry, Holloway said. Gwinnetts students come from more than 180 countries, about a third are Black, and another third are Hispanic or Latino. About a third come from economically disadvantaged families.

We want them to be represented and have a voice in how AI develops over the next few decades, when its expected to take on an even more central role in daily life, Holloway said.

One of the biggest challenges, which Holloway expects to be ongoing: There are little, if any, curricular materials out there for teaching AI to K-12 students, particularly for educators hoping to spotlight the technology in a range of subjects and grade levels.

When the district began considering its approach, no one else was thinking about this holistic idea of AI readiness, where its embedded in the classes, Holloway said. Experts were talking about specific technical AI courses, like computer science courses.

The problem is that not every kid can take those elective classes. So, every kid doesnt get access to AI, if you only address it through an elective, Holloway said. But if I embed it into all of the classes a student takes now, every single kid is going to get access to that critical learning that they need for future readiness. We just needed to create it ourselves.

To inform that work, Gwinnett school district officials reached out to higher education institutions, such as the nearby Gwinnett College, Georgia Institute of Technology, and University of Georgia in addition to other schools outside the state like Harvard University and the Massachusetts Institute of Technology. The district also turned to tech companies such as Apple, Google, IBM, and Microsoft as well as nonprofit groups AI4K12, CSForAll, and aiEDU for help.

Even though we are doing the heavy lifting, we were lucky to have a ton of people who were interested, Holloway said.

Seckinger offers a series of three progressively sophisticated elective classes focused on AI. The first will provide a broad overview of the technology, including its history and evolution, impact on society, plus an introduction to more technical aspects. The second class will go deeper, and the third will have a significant project-based component, allowing students to put their knowledge of AI towards solving real world problems.

Teacher Jason Hurd is not only leading the courses, hes playing a big part in writing them.

Thats meant developing something that doesnt exist anywhere in the country, and potentially, the world, Hurd said.

Memorie Reesman, Seckingers principal, expects a significant chunk of students will take at least one AI course. But she doesnt anticipate every Seckinger graduate will wind up in a Silicon Valley programming gig.

School and district officials think of Seckingers students in three different buckets: swimmers, who will get broad exposure to a range of AI-related topics across the curriculum; snorkelers, who might take a couple of the AI electives or delve deeper into the topic as part of another class; and scuba-divers, who will spend much of high school immersed in AI.

In all classes, teachers will be explicit about how their contentsocial studies, or even physical educationtouches on a range of topics key to helping students become AI ready, including data science, mathematical reasoning, creative problem solving, and ethics.

What I love about it is it allows us as teachers that dont teach just AI to be able to recognize that theres so much that we do already that touches on the concepts behind the technology, said Cheri Nations, who teaches environmental engineering at Seckinger. Its [about] being more intentional and authentic with it and tying it and making connections for the kids. Then, as we become more comfortable, we can start doing more of that deep diving.

Reesman has previewed how all this can work in her previous job as the principal of Glenn C. Jones Middle School, the feeder middle school in the AI cluster. The school started piloting the AI program about two years ago.

At first, Jones middle school students and teachers just played around with a few AI-related challenges during the 20-minute homeroom slot in their schedule, Reesman said, including a program from Amazon that allowed students to practice coding robots to do work in a warehouse.

Later, teachers in all subjects began mixing a bit of AI-related content into their classes. One of Reesmans favorite examples: Seventh grade science students took a concept thats long been part of their curriculumgeneticsand used coding to figure out the probability of inheriting certain genetic traits.

There are going to be some days where youre gonna see [AI] really heavily in the cluster schools, Holloway said. But it may not always be like a very obvious, hit you in the face [realization], like, Oh, were doing this in AI today. A lot of its going to show up in the culture of the school.

That culture extends even to Seckingers furniture, which isnt your typical desks in rows. Instead, most classrooms use a more flexible seating model, Holloway said.

Theyre in circles, theyre in groups. Their work is all over their wall, she said. Theyre having discussions and conversations and you might not know where the teacher is in the room because they may just be mixed in and talking with the kids. The goal is to make collaborative leadership skills and creative problem solving a central piece of every class.

Helping teachers make the cultural pivot will require time and experimentation, Holloway added.

Professional development doesnt fix everything [and] theres just a lot of priorities right now in the world of education, Holloway said. Shes explained to teachers, were going to try something different, and if we fail, thats OK because were going to pause and learn and try to improve next time.

Eventually, Gwinnett would like to see the curriculum model used throughout the district. And it could be poised to spread even further. The Georgia Department of Education worked with Gwinnett to write academic standards for the new material so that schools anywhere in the Peach State can launch their own AI courses.

South, of ISTE, expects to see more schools around the country adopt AI as a curricular focus.

There are entire universities devoted to AI in China, he said. This is already a central part of our society, and we need to prepare citizens to understand it and design it. Theres no doubt in my mind this is going to grow.

The rest is here:
Artificial Intelligence Is All Around Us. So This District Designed Its Own AI Curriculum - Education Week

Conclusions drawn by many artificial intelligence studies cannot be replicated. Here’s why this is a concern – Genetic Literacy Project

History shows civil wars to be among the messiest, most horrifying of human affairs. So Princeton professor Arvind Narayanan and his PhD student Sayash Kapoor got suspicious last year when they discovered a strand of political science research claiming to predict when a civil war will break out with more than 90 percent accuracy, thanks to artificial intelligence Yet when the Princeton researchers looked more closely, many of the results turned out to be a mirage.

Follow the latest news and policy debates on agricultural biotech and biomedicine? Subscribe to our newsletter.

They were claiming near-perfect accuracy, but we found that in each of these cases, there was an error in the machine-learning pipeline, says Kapoor. When he and Narayanan fixed those errors, in every instance they found that modern AI offered virtually no advantage.

That experience prompted the Princeton pair to investigate whether misapplication of machine learning was distorting results in other fieldsand to conclude that incorrect use of the technique is a widespread problem in modern science.

The idea that you can take a four-hour-long online course and then use machine learning in your scientific research has become so overblown, Kapoor says. People have not stopped to think about where things can potentially go wrong.

This is an excerpt. Read the original post here

See original here:
Conclusions drawn by many artificial intelligence studies cannot be replicated. Here's why this is a concern - Genetic Literacy Project

The Asia Pacific artificial intelligence market is expected to grow at the highest CAGR of 40.8% from 2022 to 2027 – GlobeNewswire

New York, Aug. 17, 2022 (GLOBE NEWSWIRE) -- Reportlinker.com announces the release of the report "Artificial Intelligence Market by Offering, Technology, Deployment Mode, Organization Size, Business Function, Vertical and Region - Global forecast to 2027" - https://www.reportlinker.com/p04412107/?utm_source=GNW In the upcoming years, it is anticipated that such developments in artificial intelligence technology would help the sector grow.Business innovators and executives are racing to achieve AIs promise of cost and time savings as well as a competitive advantage.Faster and more precise consumer behaviour data analysis empowers companies to plan their future marketing strategies and campaigns, fueling the expansion of the AI market.

Data management is assisted by AI in understanding which of their methods are inefficient and which are all the most effective. Additionally, it ensures that data reaches the intended user without being tampered by cybercriminals using man-in-the-middle, ransomware, or other forms of cyberattack.The major market players such as include IBM, Microsoft, AWS, Intel, Google, Oracle and Salesforce have adopted numerous growth strategies, which include acquisitions, new product launches, product enhancements, and business expansions, to enhance their market shares.

Based on deployment mode, cloud deployment mode to register for the largest market size during the forecast periodBased on the deployment mode, the artificial intelligence market is segmented into on-premises and cloud deployment mode.The market size of the cloud deployment mode segment is estimated to be the largest during the forecast period.

Scalability, speed, and IT security are all benefits of the cloud deployment approach.Data-driven innovation benefits greatly from the combination of AI and Cloud computing.

The popularity of the cloud deployment mode is facilitated by the cognitive powers of AI and machine learning, which thrive on massive volumes of data that are scalable and easily available in a cloud environment.

The Law segment to account for the highest CAGR during the forecast periodBased on business function, the artificial intelligence market is segmented into Finance, Security, Human Resources, Law, Marketing and Sales and other business functions.The Law segment is expected grow at a higher CAGR during the forecast period.

Large and small legal firms both are using AI technologies in growing numbers.Artificial intelligence technology, in particular Machine Learning and Natural Language Processing, are being used to boost efficiency, expand profit margins, and offer creative and effective legal counsel.

The market for AI is expanding as a result of rising litigation and rising demand to cut operational expenses.

Asia Pacific to hold highest CAGR during the forecast periodThe Asia Pacific artificial intelligence market is expected to grow at the highest CAGR of 40.8% from 2022 to 2027. In countries such as China, India, Japan, and others, the use of AI services in end user industries like manufacturing, healthcare, retail, and e-commerce can be responsible for this increase. In this region, the adoption of new and emerging technologies has gained momentum in recent years. The storage, processing, and data availability of computing systems have all risen, as well as their overall capacity. A new generation of more autonomous AI systems has been made possible by the convergence of complementary technologies, which has increased the demand for automating operations as a result of ongoing improvements in hardware and software.

Breakdown of primariesIn-depth interviews were conducted with Chief Executive Officers (CEOs), innovation and technology directors, system integrators, and executives from various key organizations operating in the artificial intelligence market. By Company: Tier I: 35%, Tier II: 45%, and Tier III: 20% By Designation: C-Level Executives: 35%, D-Level Executives: 25%, and Managers: 40% By Region: APAC: 25%, Europe: 30%, North America: 30%, MEA: 10%, Latin America: 5%The report includes the study of key players offering artificial intelligence.It profiles major vendors in the artificial intelligence market.

The major players in the artificial intelligence market include Google Inc. (US), Microsoft Corporation (US), NVIDIA Corporation (US), Intel Corporation (US), Samsung Electronics Co., Ltd. (South Korea), IBM Corporation (US), Amazon Web Services, Inc. (US), Oracle (US), Meta (US), Salesforce (US), Cisco (US), Siemens (US), Huawei (China), SAP SE (Germany), SAS Institute (US), Baidu, Inc. (China), Alibaba Cloud (China), iFLYTEK (China), and Hewlett Packard Enterprise Development LP (US).

Research CoverageThe market study covers the artificial intelligence market across segments.It aims at estimating the market size and the growth potential of this market across different segments, such as offering, technology, organization size, deployment mode, business function, vertical, and region.

It includes an in-depth competitive analysis of the key players in the market, along with their company profiles, key observations related to product and business offerings, recent developments, and key market strategies.

Key Benefits of Buying the ReportThe report would provide the market leaders/new entrants in this market with information on the closest approximations of the revenue numbers for the overall artificial intelligence market and its subsegments.It would help stakeholders understand the competitive landscape and gain more insights better to position their business and plan suitable go-to-market strategies.

It also helps stakeholders understand the pulse of the market and provides them with information on key market drivers, restraints, challenges, and opportunities.Read the full report: https://www.reportlinker.com/p04412107/?utm_source=GNW

About ReportlinkerReportLinker is an award-winning market research solution. Reportlinker finds and organizes the latest industry data so you get all the market research you need - instantly, in one place.

__________________________

Read the rest here:
The Asia Pacific artificial intelligence market is expected to grow at the highest CAGR of 40.8% from 2022 to 2027 - GlobeNewswire

Will Art Created By Artificial Intelligence Kill The Artist? – Fstoppers

Most of my photography friends have been playing around with some form of AI Art, and the results are pretty remarkable. However, as amazing as this technology is, I'm sure I am not the only one wondering if Artificial Intelligence will leave us all looking for new careers.

What exactly is artificial intelligent art? AI art is a brand new form of expression that allows users to string together a bunch of descriptive words, feed them into a machine learning program, and have the software export a one-of-a-kind, hyper-graphic image in seconds. The results aren't always what you might have imagined in your head, and more times than not, the efforts of the Ai algorithm are beyond your wildest imagination. On one hand, AI-generated art is one of the greatest inventions of modern history but on the other hand, it raises so many questions. Is AI art real art? Is the final image a creative product of the prompt writer? Who owns the rights to the final creation? Should we value it more than similar art that has taken much more time, effort, and skill?

All of these questions led me to reach out to my good friend and fellow photographer/entrepreneur Pye Jirsa. Many of you know Pye as the creative face of SLR Lounge, but he also runs a multi-seven-figure wedding business (perhaps one of the most successful wedding photography businesses in the world), and has recently started a new business venture, 12 Week Relationships, which dives into the world of relationship psychology. Needless to say, Pye is an incredibly talented creative, has a brilliant approach to business marketing, and also understands how new technologies can lead to greater success for those who become early adopters.

Since both Pye and I have explored the early beta offerings of many AI art generators, I thought it would be great to record our early thoughts, arguments, and perspectives on this crazy new form of art. Throughout this extended podcast, we find ourselves both intrigued and horrified at what this new technology will bring to the art world. Some of the topics we cover include:

These are just a few of the concepts we freely talk about in our 90-minute conversation, and I have to say, after bouncing some of my own ideas off Pye, I found myself left with even more questions than I had entering this conversation. Pye brings up some interesting points about how technology shifts in the past have left 99% of nonadopting artists to ruin from a commercial and business standpoint. He also questions how future generations will value and dedicate time to learning any specific art form when artificial intelligence can simply create something far superior and intricate than decades of human practice and mastery of the same medium. Of course, there will always be value in learning an art for fun, emotional sanctuary, and to explore your own creativity. Still, the question remains, "how will AI art change the way we use, consume, and appreciate art in the future?"

Here are a few of the images featured in the podcast created through Mid Journey

Perhaps once I have even more time to form my own thoughts about artificial art and where it is going, I will write up a full opinion piece on Fstoppers. At the moment, if I'm honest with myself, I'm not exactly sure how I truly feel about AI art generators like Mid Journey, Nightcafe, StarryAI, and Dall-E Mini. Half of me absolutely loves seeing what crazy and wacky ideas I can come up with and the resulting images AI generators can produce. The other half of me truly sees the writing on the wall and expects to both see and use AI art more and more in the future.

What are your thoughts on this new form of creativity? The flood gates aren't truly opened yet as many of the programs listed above are still in their beta state and many still require invitations to use their services. Once AI art becomes even more malleable, realistic, and widespread, do you think it will under mind the careers of many creatives or will it always remain a novelty and not compromise the skills so many of us have worked our entire lives to perfect?

If you want to share your own AI art and participate in our latest Critique the Community, check out the CTC Ai Prompt Art Page and perhaps you can win a free tutorial from the Fstoppers Store!

Original post:
Will Art Created By Artificial Intelligence Kill The Artist? - Fstoppers

Artificial Intelligence and Inventorship: An Expected Decision with Uncertain Consequences – JD Supra

The top U.S. patent court has confirmed what many were expecting in the patent community that artificial intelligence (AI) is not considered an individual according to the Patent Act and thus AI cannot be named as an inventor on a patent.

The courts ruling was the latest roadblock encountered by Dr. Stephen Thaler, who filed patent applications in several jurisdictions on a technology developed by the Autonomous Bootstrapping of Unified Sentience (DABUS) an AI system created by Dr. Thaler that mimics the neural network of a human brain. These patent applications were filed as part of the Artificial Inventor Project and were focused on protecting two inventions that were conceived by DABUS without human intervention. As such, Dr. Thaler listed DABUS as the sole inventor.

Initially, the Patent Office denied the applications as failing to list a human inventor, relying on a provision of the Patent Act that defines an inventor as the individual . . . who invented or discovered the subject matter of the invention. According to the Patent Office, the current statutes, case law, and Patent Office regulations all limit inventorship to a human and preclude a broad interpretation that would encompass an AI machine.

In September 2021, a federal court in Virginia agreed with the Patent Office. The court provided a glimpse of hope for the future, however, stating [a]s technology evolves, there may come a time when artificial intelligence reaches a level of sophistication such that it might satisfy the accepted meaning of inventorship. But that time has not yet arrived, and, if it does, it will be up to Congress to decide how, if at all, it wants to expand the scope of patent law.

On appeal, the top patent court (The Court of Appeals for the Federal Circuit) confirmed that only humans can be considered inventors under current U.S. patent laws. The decision focused on whether AI could be listed as the sole inventor and did not address instances in which humans use AI to assist with conception of an invention. As such, we may see additional litigation on the latter issue involving parties attempting to invalidate a patent based on improper inventorship.

The Federal Circuit decision only reinforces what has been decided in foreign jurisdictions. Europe and the UK have taken a similar position on AI and inventorship, although Europe has indicated that it may be possible to name the AIs user or owner as the inventor instead. Australia initially seemed to allow for AI to be an inventor, but an Australian court overturned this position in April 2022. South Africa the only jurisdiction in which patents have been granted to DABUS does not substantively review patent applications and, therefore, provides little guidance on this issue.

For now, the legal systems of the world seem to agree that AI cannot be listed as an inventor on a patent application. Although it appears that Dr. Thaler intends on appealing the decision to the Supreme Court, the outcome is not expected to change. Instead, these decisions show that legislative action will be needed to adapt the current patent laws to the quickly evolving world of AI. In the meantime, industries that rely on AI should continue involving humans in the inventive process to ensure that the inventorship includes at least one individual according to current patent laws.

[View source.]

Follow this link:
Artificial Intelligence and Inventorship: An Expected Decision with Uncertain Consequences - JD Supra

Artificial Intelligence In Drug Discovery Global Market to Grow from $1.04 Billion to $2.99 Billion by 2026 – Yahoo Finance

DUBLIN, Aug. 16, 2022 /PRNewswire/ --The "Artificial Intelligence (AI) In Drug Discovery Global Market Report 2022, By Technology, By Drug Type, By Therapeutic Type, By End-Users" report has been added to ResearchAndMarkets.com's offering.

Research and Markets Logo

The global artificial intelligence (AI) in drug discovery market is expected to grow from $791.83 million in 2021 to $1042.30 million in 2022 at a compound annual growth rate (CAGR) of 31.6%. The market is expected to reach $2994.52 million in 2026 at a CAGR of 30.2%.

The artificial intelligence (AI) in drug discovery market consists of sales of AI for drug discovery and related services. Artificial Intelligence (AI) for drug discovery is a technology that uses a simulation of human intelligence process by machines to tackle complex problems in the drug discovery process. It helps to find new molecules to identify drug targets and develop personalized medicines in the pharmaceutical industry.

The main technologies in artificial intelligence (AI) in drug discovery are deep learning and machine learning. Deep learning is a machine learning and artificial intelligence (AI) technique that mimics how humans acquire knowledge. Data science, which covers statistics and predictive modelling, incorporates deep learning as a key component.

The different drug types include small molecule, large molecules and involves various types of therapies such as metabolic disease, cardiovascular disease, oncology, neurodegenerative diseases, others. It is implemented in several end-users including pharmaceutical companies, biopharmaceutical companies, academic and research institutes, others.

The rise in demand for a reduction in the overall time taken for the drug discovery process is a key driver propelling the growth of the artificial intelligence (AI) in drug discovery market. Traditionally, it takes three to five years for animal models to identify and optimize molecules before they are evaluated in humans whereas start-ups based on AI have been identifying and designing new drugs in a matter of few days or months.

For instance, in 2020, the British start-up Exscientia and Japan's Sumitomo Dainippon Pharma have used artificial intelligence to produce an obsessive-compulsive disorder (OCD) medication, decreasing the development time from four years to less than one year. The reduction in overall time taken for the drug discovery process drives the artificial intelligence (AI) in drug discovery market's growth.

The shortage of skilled professionals is expected to hamper the AI in drug discovery market. The employees have to re-train or learn new skill sets to work efficiently on the complex AI machines to get the desired results for the drug. The shortage of skills acts as a major hindrance to drug discovery through AI, discouraging companies from adopting AI-based machines for drug discovery.

ScopeMarkets Covered:1) By Technology: Deep Learning; Machine Learning2) By Drug Type: Small Molecule; Large Molecules3) By Therapeutic Type: Metabolic Disease; Cardiovascular Disease; Oncology; Neurodegenerative Diseases; Others4) By End-Users: Pharmaceutical Companies; Biopharmaceutical Companies; Academic And Research Institutes; Others

Key Topics Covered:

1. Executive Summary

2. Artificial Intelligence (AI) In Drug Discovery Market Characteristics

3. Artificial Intelligence (AI) In Drug Discovery Market Trends And Strategies

4. Impact Of COVID-19 On Artificial Intelligence (AI) In Drug Discovery

5. Artificial Intelligence (AI) In Drug Discovery Market Size And Growth

6. Artificial Intelligence (AI) In Drug Discovery Market Segmentation

7. Artificial Intelligence (AI) In Drug Discovery Market Regional And Country Analysis8. Asia-Pacific Artificial Intelligence (AI) In Drug Discovery Market

9. China Artificial Intelligence (AI) In Drug Discovery Market

10. India Artificial Intelligence (AI) In Drug Discovery Market

11. Japan Artificial Intelligence (AI) In Drug Discovery Market

12. Australia Artificial Intelligence (AI) In Drug Discovery Market

13. Indonesia Artificial Intelligence (AI) In Drug Discovery Market

14. South Korea Artificial Intelligence (AI) In Drug Discovery Market

15. Western Europe Artificial Intelligence (AI) In Drug Discovery Market

16. UK Artificial Intelligence (AI) In Drug Discovery Market

17. Germany Artificial Intelligence (AI) In Drug Discovery Market

18. France Artificial Intelligence (AI) In Drug Discovery Market

19. Eastern Europe Artificial Intelligence (AI) In Drug Discovery Market

20. Russia Artificial Intelligence (AI) In Drug Discovery Market

21. North America Artificial Intelligence (AI) In Drug Discovery Market

22. USA Artificial Intelligence (AI) In Drug Discovery Market

23. South America Artificial Intelligence (AI) In Drug Discovery Market

24. Brazil Artificial Intelligence (AI) In Drug Discovery Market

25. Middle East Artificial Intelligence (AI) In Drug Discovery Market

26. Africa Artificial Intelligence (AI) In Drug Discovery Market

27. Artificial Intelligence (AI) In Drug Discovery Market Competitive Landscape And Company Profiles

28. Key Mergers And Acquisitions In The Artificial Intelligence (AI) In Drug Discovery Market

29. Artificial Intelligence (AI) In Drug Discovery Market Future Outlook and Potential Analysis

30. Appendix

Companies Mentioned

IBM Corporation

Microsoft

Atomwise Inc.

Deep Genomics

Cloud Pharmaceuticals

Insilico Medicine

Benevolent AI

Exscientia

Cyclica

BIOAGE

Numerate

Numedii

Envisagenics

twoXAR

OWKIN Inc.

XtalPi

Berg LLC

Google

Verge Genomics

For more information about this report visit https://www.researchandmarkets.com/r/5onrkw

Media Contact:

Research and MarketsLaura Wood, Senior Managerpress@researchandmarkets.com

For E.S.T Office Hours Call +1-917-300-0470For U.S./CAN Toll Free Call +1-800-526-8630For GMT Office Hours Call +353-1-416-8900

U.S. Fax: 646-607-1907Fax (outside U.S.): +353-1-481-1716

Logo: https://mma.prnewswire.com/media/539438/Research_and_Markets_Logo.jpg

Cision

View original content:https://www.prnewswire.com/news-releases/artificial-intelligence-in-drug-discovery-global-market-to-grow-from-1-04-billion-to-2-99-billion-by-2026--301606403.html

SOURCE Research and Markets

Read the rest here:
Artificial Intelligence In Drug Discovery Global Market to Grow from $1.04 Billion to $2.99 Billion by 2026 - Yahoo Finance

Ex-prosecutor in Boston indicted on NYC rape charges – New York Daily News

A former prosecutor and prominent voice in the criminal justice reform movement was indicted Tuesday for allegedly raping a woman as she slept inside a Chelsea hotel room in 2017.

Adam Foss, 42, a former assistant district attorney for the Suffolk County prosecutors office in Boston, Mass., pleaded not guilty to rape and sexual abuse charges at his state Supreme Court arraignment in Manhattan. A judge released him under the condition he surrender his passport.

Foss is the founder of Prosecutor Impact, a nonprofit whose stated mission is to improve community safety through educating and training criminal prosecutors. Its website was down Tuesday.

Adam Foss is pictured speaking at the Berkshire Probate & Family Court in Pittsfield, Mass., in 2019. (Stephanie Zollshan/AP)

Manhattan prosecutors charge that Foss met a woman hed been speaking with on the phone and in texts for a month at the INNSiDE New York NoMad hotel on Oct. 21, 2017. He raped her as she slept and after she had repeatedly rejected his sexual advances, according to charging documents.

The 25-year-old victim was incapable of consent by reason of being physically helpless, according to the indictment.

Foss was publicly accused of rape in a 2020 online essay published by singer-songwriter Raegan Sealy on Medium, titled The Wolf and the Whisper Network. Prosecutors declined to confirm whether she was the victim in the case.

Describing Foss as a rapist in a feminist tee, Sealy wrote that she met him at a speaking event attended by Jennifer Garner, Cynthia Nixon, and Chelsea Manning, and a week later he followed up, wanting to hang out with her.

As it happens

Get updates on the coronavirus pandemic and other news as it happens with our free breaking news email alerts.

A month after texting back and forth, Sealy wrote, her first date with Foss ended in a nightmare. She alleged that when Foss wouldnt take no for an answer, he had sex with her while she was unconscious.

In 2017, I was raped by a progressive, liberal, acclaimed social justice advocate, wrote Sealy. [Behind] Adam the feminist lives Adam the rapist. Not just Adam the player not even Adam the predator. Adam, the rapist. Adam the destroyer.

Sealy could not be reached for comment.

In 2021, Suffolk County District Attorney Rachael Rollins issued a public apology to two unnamed women in her office who were treated less than professionally, if not criminally while working under him.

Robert Gottlieb, Fosss lawyer, could not be reached for comment.

I thank this brave survivor, who had the courage to come forward and share her story, said District Attorney Alvin Bragg.

Continued here:
Ex-prosecutor in Boston indicted on NYC rape charges - New York Daily News