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AI

NATO launches AI strategy and $1B fund as defense race heats up

The North Atlantic Treaty Organization (NATO), the military alliance of 30 countries that border the North Atlantic Ocean, this week announced that it would adopt its first AI strategy and launch a “future-proofing” fund with the goal of investing around $1 billion. Military.com reports that U.S. Defense Secretary Lloyd Austin will join other NATO members in Brussels, Belgium, the alliance’s headquarters, to formally approve the plans over two days of talks.

Speaking at a news conference, Secretary-General Jens Stoltenberg said that the effort was in response to “authoritarian regimes racing to develop new technologies.” NATO’s AI strategy will cover areas including data analysis, imagery, cyberdefense, he added.

NATO said in a July press release that it was “currently finalizing” its strategy on AI” and that principles of responsible use of AI in defense will be “at the core” of the strategy. Speaking to Politico in March, NATO assistant secretary general for emerging security challenges David van Weel said that the strategy would identify ways to operate AI systems ethically, pinpoint military applications for the technology, and provide a “platform for allies to test their AI to see whether it’s up to NATO standards.” van Weel said.

“Future conflicts will be fought not just with bullets and bombs, but also with bytes and big data,” Stoltenberg said. “We must keep our technological edge.”

NATO’s overtures come after a senior cybersecurity official at the Pentagon resigned in protest because of the slow pace of technological development at the department. Speaking to the press last week, Nicolas Chaillan, former chief software officer at the Air Force, said that the U.S. has “no competing fighting chance against China” in 15 to 20 years, characterizing the AI and cyber defenses in some government agencies as being at “kindergarten level.”

In 2020, the U.S. Department of Defense (DoD) launched the AI Partnership for Defense, which consists of 13 countries from Europe and Asia to collaborate on AI use in the military context. More recently, the department announced that it plans to invest $874 million next year in AI-related technologies as a part of the army’s $2.3 billion science and technology research budget.

Much of the DoD’s spending originates from the Joint Artificial Intelligence Center (JAIC) in Washington, D.C., a government organization exploring the use and applications of AI in combat. (In news related to today’s NATO announcement, JAIC is expected to finalize its AI ethics guidelines by the end of this month.) According to an analysis by Deltek, the DoD set aside $550 million of AI obligations awarded to the top ten contractors and defense accounted for 37% of total AI spending by the U.S. government, with contractors receiving the windfall.

Fearmongering

While U.S. — and now NATO — officials grow more vocal about China’s supposed dominance in military and defense AI, research suggests that their claims somewhat exaggerate the threat. A 2019 report from the Center for Security and Emerging Technology (CSET) shows that China is likely spending far less on AI than previously assumed, between $2 billion and $8 billion. That’s as opposed to the $70 billion figure originally shared in a speech by a top US Air Force general in 2018.

While Baidu, Tencent, SenseTime, Alibaba, and iFlytek, and some of China’s other largest companies collaborate with the government to develop AI for national defense, MIT Tech Review points out that Western nations’ attitudes could ultimately hurt U.S. AI development by focusing too much on military AI and too little on fundamental research. A recent OneZero report highlighted the way that the Pentagon uses adversaries’ reported progress to scare tech companies into working with the military, framing government contracting as an ideological choice to support the U.S. in a battle against China, Russia, and other competing states.

Speaking at the Center for Strategic and International Studies Global Security Forum in January 2020, secretary of defense Mike Esper said that DoD partnerships with the private sector are vital to the Pentagon’s aim to remain a leader in emerging technologies like AI. Among others, former Google CEO Eric Schmidt — a member of the DoD’s Defense Innovation Board — has urged lawmakers to bolster funding in the AI space while incentivizing public-private partnerships to develop AI applications across government agencies, including military agencies.

Contractors have benefited enormously from the push — Lockheed Martin alone netted $106 million in 2020 for an AI-powered “cyber radar” initiative. Tech companies including Concur, Microsoft, and Dell have contracts with U.S. Immigration and Customs Enforcement, with Microsoft pledging — then abandoning in the face of protests — to build versions of its HoloLens headsets for the U.S. Army. (Microsoft this month agreed to commission an independent human rights review of some of its deals with government agencies and law enforcement.)

Amazon and Microsoft fiercely competed for — and launched a legal battle over — the DoD’s $10 billion Joint Enterprise Defense Infrastructure (JEDI) contract, which was canceled in July after the Pentagon launched a new multivendor project. Machine learning, computer vision, facial recognition vendors including TrueFace, Clearview AI, TwoSense, and AI.Reverie also have contracts with various U.S. army branches.

For some AI and data analytics companies, like Oculus cofounder Palmer Luckey’s Anduril and Palantir, military contracts have become a top source of revenue. In October, Palantir won most of an $823 million contract to provide data and big analytics software to the U.S. army. And in July, Anduril said that it received a contract worth up to $99 million to supply the U.S. military with drones aimed at countering hostile or unauthorized drones.

While suppliers are likely to remain in abundance, the challenge for NATO will be aligning its members on AI in defense. The U.S. and others, including France and the U.K., have developed autonomous weapons technologies, but members like Belgium and Germany have expressed concerns about the implications of the technologies.

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AI

AI Weekly: GoodAI aims to fund research on fundamental AI challenge

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There’s a growing need for investment in foundational AI technologies. With deep learning potentially approaching computational limits and subfields like natural language running up against intractable technical barriers, novel AI and machine learning techniques have arguably never been in higher demand.

NYU psychologist Gary Marcus, Google software engineer Francois Chollet, and Facebook head of AI Jerome Pesenti, among others, have argued that the lack of progress isn’t surprising, as researchers face challenges both algorithmic and scientific. Even the most sophisticated AI models can suffer from catastrophic forgetting, or a tendency to abruptly forget previously learned information, in addition to a lack of reproducibility, explainability, stability, and reliability.

That’s why Marek Rosa, a Slovakian entrepreneur and computer programmer, founded GoodAI, a company dedicated to the research and development of general artificial intelligence (AGI). He’s the CEO and founder of Keen Software House, an independent video game design studio with a headquarters in Prague, the capital of the Czech Republic.

Rosa founded GoodAI in 2014 with a $10 million investment, then announcing the company publicly and its first research roadmap in 2015 and 2016, respectively. In 2017, he founded the General AI Challenge, pledging $5 million in prize money to tackle critical research problems in “human-level” AI development.

GoodAI now employs around 20 researchers and engineers. Its newest endeavor is the GoodAI Grants Initiative, which aims to fund efforts in areas like curiosity and continual learning. To date, the GoodAI Grants Initiative has awarded over $650,000 — all from Rosa — to nine projects that GoodAI considers a part of its roadmap to general AI.

“What makes us different [from other grant organizations] is our openness and flexibility and our willingness to work with potential grantees in creating a fitting proposal,” GoodAI PR manager Will Millership told VentureBeat in an email interview. “We really don’t want to be limited in who we work with by bureaucracy and therefore we work with individual scientists, groups of researchers, private companies, and even individual students. We do a lot of work to make sure that all the intellectual property from the projects is shared but this doesn’t necessarily mean completely open. Each agreement in place aims to respect the academic and business interests of both GoodAI and the receivers of the grants.”

GoodAI grant projects

In December 2019, Rosa and the GoodAI team published Badger, a unifying AI architecture defined by a principle GoodAI calls “modular lifelong learning.” Badger, which outlines the direction of GoodAI’s research, seeks to create a system of AI agents capable of adapting to a growing, open-ended range of tasks while remaining able to reuse knowledge acquired in previous tasks.

“Our aim is to develop safe general AI — as fast as possible — to help humanity and understand the universe,” Millership said. “We see the creation of human-level AI as the biggest challenge to mankind and a task far beyond that of an individual researcher or research group. That’s why we believe collaboration — and not competition — is the best way forward.”

Among GoodAI’s grant recipients is Deepak Pathak, an assistant professor at Carnegie Mellon University who’s taking inspiration from developmental psychology and particularly how curiosity drives human’s early developmental learning. Another is Ferran Alet, a Ph.D. student at MIT’s Computer Science and Artificial Intelligence Laboratory, who’s aiming to make an AI model that generalizes to new tasks in new environments from small amounts of data and previous experiences.

GoodAI’s ambition — AGI, or the hypothetical intelligence of a machine with the capacity to understand or learn from any task — has its detractors. Facebook chief AI scientist Yann LeCun believes that it can’t exist, because there’s no such thing as general intelligence. He argues that even human intelligence is very specialized, requiring many different systems to accomplish different individual tasks.

In something of a rebuttal to this, GoodAI recently released its latest research roadmap, which spotlights some of the technical challenges related to creating human-level or general AI. GoodAI asserts that AGI must “learn to learn” and engage in lifelong learning, both continuously and at a gradual cadence. It also believes that AGI should be able to engage in open-ended exploration and self-invent goals as well as generalize “out of distribution” and extrapolate to new problems.

“Each of these features reflects the ways in which humans learn throughout their lifetime and therefore we see them as key to creating AI that’s able to generalize to new problems in different environments, much like humans do,” Millership said. “We [plan to] work closely with the grantees during their projects, offering support if they need it, and [put] on a seminar in the summer, where all grantees can share their ideas and projects. We’re trying to create an international community of researchers crossing the boundaries of academia and industry.”

Despite recent breakthroughs in solving barriers to AGI, it’s clear the road to more humanlike AI will be long and winding. However, efforts like GoodAI, along with nonprofit organizations and open communities like ContinualAI and EleutherAI, look to accelerate progress by tapping into the broader pool of AI and machine learning expertise.

For AI coverage, send news tips to Kyle Wiggers — and be sure to subscribe to the AI Weekly newsletter and bookmark our AI channel, The Machine.

Thanks for reading,

Kyle Wiggers

AI Staff Writer

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AI

OpenAI launches $100M startup fund with Microsoft

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OpenAI today launched the OpenAI Startup Fund, a $100 million fund to, in the words of OpenAI, “help AI companies have a profound, positive impact on the world.” The fund is managed by OpenAI, with investment from Microsoft and other partners, and OpenAI says that companies selected for it will get early access to future OpenAI systems, support from OpenAI’s team, and credits on Microsoft Azure.

According to Sam Altman, CEO of OpenAI and the former president of Y Combinator, the OpenAI Startup Fund will make “big, early bets” on a relatively small number of companies, likely no more than 10. It’ll look to partner with early-stage startups in fields where AI can have a “transformative” effect — like health care, climate change, and education — and where AI tools can empower people by helping them be more productive, like personal assistance and semantic search.

“We think that helping people be more productive with new tools is a big deal. And we can imagine brand new interferences that weren’t possible a year ago,” Altman said. “We’re really excited about the opportunity for startups, for the industry and for people everywhere who can put AI to work improving their lives.”

Microsoft partnership

The OpenAI Startup Fund further extends Microsoft’s collaboration with San Francisco, California-based OpenAI. Roughly a year ago, Microsoft announced it would invest $1 billion in OpenAI to jointly develop new technologies for Microsoft’s Azure cloud platform and to “further extend” large-scale AI capabilities that “deliver on the promise” of artificial general intelligence. In exchange, OpenAI agreed to license some of its intellectual property to Microsoft, which the company would then package and sell to partners, and to train and run AI models on Azure as OpenAI worked to develop next-generation computing hardware.

In the months that followed, OpenAI released a Microsoft Azure-powered API that allows developers to explore GPT-3’s capabilities. And toward the end of 2020, Microsoft announced that it would exclusively license GPT-3 to develop and deliver AI solutions for customers, as well as create new products that harness the power of natural language generation.

This week, Microsoft announced that it would “deeply integrate” GPT-3 with Power Apps, its low-code app development platform — specifically for formula generation. The AI-powered features will allow a user building an ecommerce app, for example, to describe a programming goal using conversational language like “find products where the name starts with ‘kids.’”

Beyond Microsoft, GPT-3 is now being used in more than 300 different apps by “tens of thousands” of developers and producing over 4.5 billion words per day, according to OpenAI. A startup called Viable is using GPT-3 to analyze customer feedback, identifying “themes, emotions, and sentiment from surveys, help desk tickets, live chat logs, reviews, and more”; Fable Studio is leveraging the model to create dialogue for VR experiences; and Algolia is using it to improve its web search products.

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AI

China fund managers rely on AI to manage trading data and pick stocks

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(Reuters) — Chinese fund managers, grappling with a rapidly-growing list of publicly-traded securities and mountains of data, are rapidly embracing machine learning and other types of artificial intelligence (AI) to boost efficiency and bolster returns.

From using computers for analyzing news and research reports and crunching numbers to getting robots to pick stocks, the move comes as foreign players are expanding their footprint in China’s $3.4-trillion mutual fund industry.

While AI has already been widely used in China’s mammoth e-commerce and manufacturing sectors, it is now being adopted by asset managers as Beijing aims to digitize the economy further and close the technology gap with the western world.

Last week, Zheshang Fund Management launched a fund that uses robots to predict the market outlook and select stocks. It came after China Asset Management (ChinaAMC) announced its partnership with Toronto-based AI company Boosted.ai.

“I think it’s a must. Every major player is actively looking for AI solutions. The competition is really tough,” said Bill Chen, chief data officer of ChinaAMC, which managed $246 billion worth of assets at the end of last year.

Global fund managers such as BlackRock have been using computer artificial intelligence (AI) to analyze fundamentals, market sentiment and macroeconomic policies in the last couple of years to get an investment edge.

“Companies like BlackRock have very powerful, advanced technology. They are leading us in AI for sure, by at least several years,” said Chen. “But I think we understand the Chinese market better.”

Fund managers’ increased usage of AI in the world’s second-largest economy comes as Beijing is stepping up digitalization drive, a trend accelerated by the COVID-19 pandemic and as it increasingly clashes with the West over technology policy.

China’s stock market listing reforms have boosted the number of public companies, leading to a data explosion that also fuels demand for AI, said Zhou Yu, chief product officer of ABC Fintech, a Beijing-based AI company.

ABC Fintech counts asset managers such as China Universal Asset Management and Hwabao WP Fund Management Co as clients, and serves as their data factory, Yu said.

Regulatory challenges

Growing investments into AI are also being fueled by early signs of success.

Zheshang Fund’s first AI-powered fund, Zheshang Intelligent Industry Preferred Hybrid Fund has gained 68.34% since its launch in Sept 2019, according to its Q1 report, compared with a 21.64% gain in its benchmark, which is a combination of stock and bond indexes.

The fund has built an “AI Beehive strategy model” in which robots team up like humans to buy stocks. More than 400 robots compete for the right to make decisions as their models constantly evolve through trial and error.

Peter Shepard, managing director at MSCI Research, said that instead of providing super-human intelligence, AI provides super-human scale that will open up fresh sources of information that drive new levels of insight and efficiency.

“These new tools on their own can’t predict the future any better than people can, but they are key to unlocking new, alternative and unstructured data sets that will continue to transform the investment process.”

“AI will be an important edge,” said Larry Cao, senior director at CFA Institute, who authored several reports on AI-powered investing. “The hard truth with AI is that the bigger firms can invest a lot more resources.”

Some Chinese industry officials, however, expressed concerns that the use of machine learning algorithms to pick stocks and better returns could run into regulatory challenges.

“From a regulatory perspective, you need to go through a lot of compliance procedures. You need to write reports on your decision making. Some AI-powered models are like black boxes, and unexplainable,” said Yu of ABC Fintech.

“That’s hardly acceptable to regulators.”

As learning algorithms are increasingly used in trading rooms, local fund managers are working with regulators to try to design new standards for the industry.

“One of the main barriers we face … is that we are so highly regulated,” ChinaAMC’s Chen said. “Every decision you make, you have to be responsible for that decision, and you should be able to explain a decision when you lose money.”

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AI

U.S. Senate committee revised a draft bill to fund AI, quantum, biotech

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(Reuters) -U.S. Senate committee leaders have drafted a compromise $110 billion measure for basic and advanced technology research and science over five years and the creation of a White House chief manufacturing officer in the face of rising competitive pressure from China, according to a copy of the 131-page draft legislation seen on Friday by Reuters.

The revised draft bill by Senate Commerce Committee Chair Maria Cantwell and the committee’s top Republican Roger Wicker is set to be debated by the committee on Wednesday.

The bipartisan “Endless Frontier” bill would authorize most of the money, $95 billion, over five years to invest in basic and advanced research, commercialization, and education and training programs in key technology areas, including artificial intelligence, semiconductors, quantum computing, advanced communications, biotechnology and advanced energy.

The measure, sponsored by Senate Majority Leader Chuck Schumer, a Democrat, Republican Senator Todd Young and others, would also authorize another $10 billion to designate at least 10 regional technology hubs and create a supply chain crisis-response program to address issues like the shortfall in semiconductor chips harming auto production.

The revised version also would create a new Senate-confirmed chief manufacturing officer who would serve in the executive office of the president and would head a new Office of Manufacturing and Industrial Innovation Policy.

It would also direct the Commerce Department to establish “a supply chain resiliency and crisis response program,” including “the ability of supply chains to resist and recover in the face of shocks, including pandemic and biological threats, cyberattacks, extreme weather events, terrorist and geopolitical attacks, great power conflict, and other threats.”

The bill also seeks to boost basic research to accelerate innovation to advance critical minerals mining strategies and technologies to eliminate “national reliance on minerals and mineral materials that are subject to supply disruptions.”

The draft bill would also block Chinese companies from participating in the Manufacturing USA program without a waiver. The program is a government and company-led effort to build up industrial competitiveness, cut energy use, and strengthen U.S. national security.

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Tech News

Facebook takes on Substack with $5m fund for indie writers in US

Last month, Facebook officially announced its previously rumored newsletter platform similar to competing services like Substack and Ghost. Getting writers to make the switch to a new platform may take some effort, however, and so Facebook is back with another announcement: a $5 million fund specifically for independent writers located in the United States.

According to Facebook, the funds are earmarked for ‘local journalists’ who want to move their work to the company’s new publishing platform. The company is accepting applications from interested writers over the next few weeks, noting that some people who apply may get ‘further consideration for an opportunity’ involving a multi-year deal and monetization tools, among other things.

For their part, the writers who are accepted will need to regularly publish work that applies to a local community while engaging with readers using tools like Groups. The core requirements for potentially writing on Facebook’s platform include being an independent writer who lives in the US and covers public interest local news.

Facebook notes that it plans to prioritize writers who will ‘extensively’ cover audiences of color, locations that don’t already get coverage from an existing media company, and writers who don’t already work for a different news publisher.

Writers who submit an application can expect to get updates in June; check out the full Facebook Journalism Project page for all the details. The company notes that its new platform related to this project will arrive in the US ‘in the coming months.’

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AI

Big data analytics firm Dataminr raises $475M to fund platform expansion

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Dataminr, a New York-based company specializing in AI that provides real-time information to customers, today announced it has raised $475 million at a post-money valuation of $4.1 billion. The company says the capital will be used to accelerate the growth of its corporate business line, which spans physical safety and security, reputation risk and crisis management, business intelligence, and cyber threat detection. Dataminr also plans to make investments in internationalization, expanding its private and public sector sales footprint across the Europe and Asia Pacific regions.

Data analytics is the science of analyzing raw data to extract meaningful insights. Market Research Future predicts that the global data analytics market will be valued at over $132 billion by 2026. A range of organizations can use data to boost their marketing strategies, increase their bottom line, personalize their content, and better understand their customers. Businesses that use big data increase their profits by an average of 8%, according to a survey conducted by BARC research.

Dataminr, which was founded in 2009 by Yale graduates Ted Bailey, Sam Hendel, and Jeff Kinsey, offers an information discovery platform that detects patterns of emerging events and information from public data signals. While in college, Bailey studied the impact of real-time data on society and was specifically interested in how technologies change the way humans become aware of world events. In 2008, Bailey became fascinated by the new wave of platforms like YouTube and Twitter and realized these tools gave people the ability to capture events as they’re happening. Bailey also realized these platforms might be able to fill in information gaps during events if scaled.

Today Dataminr claims to perform trillions of daily computations across billions of public data inputs in more than 150 languages, drawing on text, images, videos, logs from sensors, and multimodal combinations of these formats from over 100,000 sources, spanning blogs, global and regional social media sites, web forums, local digital media, radio and audio transmissions, the deep and dark web, cyber signals, and internet of things devices.

Dataminr

Dataminr develops products targeting businesses, the public sector, and newsrooms, all of which use a combination of AI to parse the public data it regularly analyzes. Among the techniques the company employs are natural language processing, computer vision, audio processing and classification, and anomaly detection, all of which help surface “high-impact” events and emerging risks in real time. For example, one of the world’s largest airlines uses the platform to detect events that require adjustments in flight schedules, Dataminr says.

“Dataminr has invested highly in deep learning in the last few years, which has enabled the company to pioneer new AI signal detection fields, like multimodal fusion AI, which synthesizes real-time inputs in different data formats into multi-variable event detection models,” a spokesperson told VentureBeat via email. “Dataminr can take advantage of its now over 11-year proprietary data archive, which holds the patterns of how all events were recorded in digital data and serves as the essential foundation upon which Dataminr can continue to train and update its AI models. On average, Dataminr signals on breaking events are delivered to our clients nearly four hours ahead of a wire service like the Associated Press.”

Dataminr first came into the public eye in 2011, when it issued an alert that Osama bin Laden had been killed 23 minutes faster than major news organizations. In 2019, Dataminr claimed to have detected the first signs of the COVID-19 outbreak in Wuhan on local Chinese social media platforms like Weibo and went to identify clusters indicating future spikes in 14 different U.S. states.

But Dataminr has often flirted with controversy. In 2020, the Intercept released a report showing that police departments used the company’s services for surveillance during the George Floyd protests, including accessing social media posts about protest locations and actions. The piece noted that the monitoring seemed at odds with claims from Dataminr that the company would neither engage in nor facilitate surveillance. This followed a string of bad press in 2016, when Twitter cut off geospatial data access for police intelligence centers.

Dataminr

Dataminr’s public image problems haven’t impacted business, though, with the roughly 650-person company reporting a doubling in revenue three years in a row from its corporate enterprise business line. The company’s clients include CNN, USA Today, the United Nations, Airbus, Shell, and the New York City Office of Emergency Management, among others.

“Large corporate clients are always discovering new use cases for our signals as they adopt Dataminr’s platform more broadly across their organization,” Bailey told VentureBeat via email. “As you can imagine, knowing about what is happening in the world faster than ever before possible, and at a scope unparalleled in human history, has a wide range of multi-dimensional use cases for corporate enterprises.”

Existing investors Valor Equity Partners, Morgan Stanley Tactical Value Fund, MSD Capital, The Pritzker Organization, DNS Capital, and Moore Capital Management participated in Dataminr’s latest funding round. It brings the company’s total raised to date to over $1.05 billion, following a $391.6 million series E round in June 2018.

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