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A Free Massive New Language Model; Moder Data Management; Actionable AI for NATO; AI Models are still Racist; $157 Million worth of ETH Burned!

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I hope that you enjoy the latest AI news and insights, don't forget to comment with your feedback. From this week you can find some interesting stuff added to the last section. But they have had a hard time shaking infighting and controversy over a variety of issues. Biased datasets are often the source for why AI models are also biased. "Adoption and scaling aren't things you add at the tail end of a project; they're where you need to start," Join 6000 aspiring Data Scientists to watch this FREE 75-minute session.


Artificial intelligence in cybersecurity - Dataconomy

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Artificial intelligence in cybersecurity is a must-have combination for organizations nowadays. Artificial intelligence (AI) assists under-resourced security operations analysts in keeping pace with attacks, and this technology will have a greater role as cyberattacks increase in volume and complexity. AI technologies, such as machine learning and natural language processing that analyze millions of research papers, blogs, and news stories, provide rapid insights to cut through the noise of daily alerts. AI provides analysts with a method to connect the dots between threats. The enterprise attack surface continues to expand and get more complex.


Modern Computing: A Short History, 1945-2022

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Inspired by A New History of Modern Computing by Thomas Haigh and Paul E. Ceruzzi. But the selection of key events in the journey from ENIAC to Tesla, from Data Processing to Big Data, is mine. This was the first computer made by Apple Computers Inc, which became one of the fastest growing ... [ ] companies in history, launching a number of innovative and influential computer hardware and software products. Most home computer users in the 1970s were hobbyists who designed and assembled their own machines. The Apple I, devised in a bedroom by Steve Wozniak, Steven Jobs and Ron Wayne, was a basic circuit board to which enthusiasts would add display units and keyboards. April 1945 John von Neumann's "First Draft of a Report on the EDVAC," often called the founding document of modern computing, defines "the stored program concept." July 1945 Vannevar Bush publishes "As We May Think," in which he envisions the "Memex," a memory extension device serving as a large personal repository of information that could be instantly retrieved through associative links.


Pentagon hires Lyft machine learning expert Craig Martell as its first chief digital and AI officer - SiliconANGLE

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The Department of Defense today announced that the Pentagon has hired Lyft Inc. head of machine learning Craig Martell as its first-ever chief digital and artificial intelligence officer. Martell will head up the DOD's Chief Digital and AI Office, which was created in December in order to centralize oversight of its data and AI initiatives under a single office in the Pentagon. As the person in charge of the CDAO, Martell will report directly to Deputy Secretary of Defense Kathleen Hicks. The CDAO launched with limited operational capability in February and is expected to achieve full operational capability by the end of June, FedScoop reported. He also has prior U.S. military experience thanks to his service as a tenured computer science professor at the Naval Postgraduate School, where he specialized in natural language processing.


The Pentagon's new AI chief is a former Lyft executive

Engadget

The Pentagon is still new to wielding artificial intelligence, and it's looking to an outsider for help. Breaking Defense has learned Lyft machine learning head Craig Martell is joining the Defense Department as its Chief Digital and Artificial Intelligence Officer (CDAO). He'll lead the American military's strategies for AI, analytics and data, and should play a key part in a Joint All-Domain Command and Control initiative to improve multi-force combat awareness through technology. Martell is a partial outsider. While he directed the Naval Postgraduate School's AI-driven Natural Language Processing Lab for 11 years, he hasn't served in military leadership.


Gaming the Known and Unknown via Puzzle Solving With an Artificial Intelligence Agent

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Researchers design multiple strategies for an artificial intelligent (AI) agent to solve a stochastic puzzle like Minesweeper. For decades, efforts in solving games had been exclusive to solving two-player games (i.e., board games like checkers, chess-like games, etc.), where the game outcome can be correctly and efficiently predicted by applying some artificial intelligence (AI) search technique and collecting a massive amount of gameplay statistics. However, such a method and technique cannot be applied directly to the puzzle-solving domain since puzzles are generally played alone (single-player) and have unique characteristics (such as stochastic or hidden information). So then, a question arose as to how the AI technique can retain its performance for solving two-player games but instead applied to a single-agent puzzle? For years, puzzles and games had been regarded as interchangeable or one part of the other.


CITP Seminar: Amy Winecoff - Today's Machine Learning Needs Yesterday's Social Science - Center for Information Technology Policy

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Click here to join the seminar. Research on machine learning (ML) algorithms, as well as on their ethical impacts, has focused largely on mathematical or computational questions. However, for algorithmic systems to be useful, reliable, and safe for human users, ML research must also wrangle with how users' psychology and social context affect how they interact with algorithms. This talk will address how novel research on how people interact with ML systems can benefit from decades-old ideas in social science. The first part of the talk will address how well-worn ideas from psychology and behavioral research methods can inform how ML researchers develop and evaluate algorithmic systems.


Council Post: Your AI Doesn't Really Understand You

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Charles Simon, BSEE, MSCs, is the founder and CEO of FutureAI. Most of us interact with artificial intelligence (AI) on a daily basis, whether we realize it or not. Every time you ask Alexa or Siri a question or turn to Google to settle a bar bet on who owns the National Football League's record for most career touchdowns (the answer, by the way, is Jerry Rice), you're using AI. In the business world, AI is ubiquitous. From AI bots that can identify, evaluate, and make recommendations for streamlining business processes to cybersecurity systems that continuously monitor data input patterns in order to thwart cyberattacks, AI repeatedly has demonstrated its capacity for processing and analyzing reams of data faster and more accurately than a human ever could.


Government Deep Tech 2022 Top Funding Focus Explainable AI, Photonics, Quantum

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DARPA, In-Q-Tel, US National Laboratories (examples: Argonne, Oak Ridge) are famous government funding agencies for deep tech on the forward boundaries, the near impossible, that have globally transformative solutions. The Internet is a prime example where more than 70% of the 7.8 billion population are online in 2022, closing in on 7 hours daily mobile usage, and global wealth of $500 Trillion is powered by the Internet. There is convergence between the early bets led by government funding agencies and the largest corporations and their investments. An example is from 2015, where I was invited to help the top 100 CEOs, representing nearly $100 Trillion in assets under management, to look ten years into the future for their investments. The resulting working groups, and private summits resulted in the member companies investing in all the areas identified: quantum computing, block chain, cybersecurity, big data, privacy and data, AI/ML, future in fintech, financial inclusion, ...


Government Deep Tech 2022 Top Funding Focus Explainable AI, Photonics, Quantum

#artificialintelligence

DARPA, In-Q-Tel, US National Laboratories (examples: Argonne, Oak Ridge) are famous government funding agencies for deep tech on the forward boundaries, the near impossible, that have globally transformative solutions. The Internet is a prime example where more than 70% of the 7.8 billion population are online in 2022, closing in on 7 hours daily mobile usage, and global wealth of $500 Trillion is powered by the Internet. There is convergence between the early bets led by government funding agencies and the largest corporations and their investments. An example is from 2015, where I was invited to help the top 100 CEOs, representing nearly $100 Trillion in assets under management, to look ten years into the future for their investments. The resulting working groups, and private summits resulted in the member companies investing in all the areas identified: quantum computing, block chain, cybersecurity, big data, privacy and data, AI/ML, future in fintech, financial inclusion, ...