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Andy and Dave discuss the latest in AI news and research, including a proposal from the Ada Lovelace Institute with 18 recommendations to strengthen the EU AI Act. [0:57] NVidia updates its Neural Radiance Fields to Instant NeRF, which can reconstruct a 3D scene from 2D images nearly 1000 times faster than other implementations. [2:53] Nearly 100 Chinese-affiliated researchers publish a 200-page position paper about large-scale models, a "roadmap." [4:13] In research, GoogleAI introduces PaLM (Pathway Language Model), at 540B parameters, which demonstrates the ability for logical inference and joke explanation. [7:09] OpenAI announces DALL-E 2, the successor to its previous image-from-text generator, which is no longer confused by mislabeling an item; though interestingly demonstrates greater resolution and diversity to similar technology from OpenAI, GLIDE, but not rated as well by humans, and DALL-E 2 still has challenges with 'binding attributes.' [11:32] A white paper from Gary Marcus look at 'Deep Learning Is Hitting a Wall: What would it take for AI to make real progress?' which includes an examination of a symbol-manipulation system that beat the best deep learning systems at playing ASCII game NetHack. [16:10] Professor Chad Jenkins from the University of Michigan returns to discuss the latest developments, including the upcoming Department of Robotics, and a robotics undergraduate degree. [19:10] https://www.cna.org/CAAI/audio-video
https://www.cna.org/news/AI-Podcast
Andy and Dave discuss the latest in AI news and research, starting with the Aircrew Labor In-Cockpit Automation System (ALIAS) program from DARPA, which flew a UH-60A Black Hawk autonomously and without pilots on board, to include autonomous (simulated) obstacle avoidance [1:05]. Another DARPA program, Robotic Autonomy in Complex Environments with Resiliency (RACER) entered its first phase, focused on high-speed autonomous driving in unstructured environments, such as off-road terrain [2:39]. The National Science Board releases its State of U.S. Science and Engineering 2022 report, which shows the U.S. continues to lose its leadership position in global science and engineering [4:30]. The Undersecretary of Defense for Research and Engineering, Heidi Shyu, formally releases its technology priorities, 14 areas grouped into three categories: seed areas, effective adoption areas, and defense-specific areas [6:31]. In research, OpenAI creates InstructGPT in an attempt to align language models to follow human instructions better, resulting in a model with 100x fewer parameters than GPT-3 and provided a user-favored output 70% of the time, though still suffering from toxic output [9:37]. DeepMind releases AlphaCode, which has succeeded in programming competitions with an average ranking in the top 54% across 10 contests with more than 5,000 participants each though it approaches the problem through more of a brute-force approach [14:42]. DeepMind and the EPFL's Swiss Plasma Center also announce they have used reinforcement learning algorithms to control nuclear fusion (commanding the full set of control coils of a tokamak magnetic controller). Venture City publishes Timelapse of AI (2028 – 3000+), imagining how the next 1,000 years will play out for AI and the human race [18:25]. And finally, with the Russia-Ukraine conflict continuing to evolve, CNA's Russia Program experts Sam Bendett and Jeff Edmonds return to discuss what Russia has in its inventory when it comes to autonomy and how they might use it in this conflict, wrapping up insights from their recent paper on Russian Military Autonomy in a Ukraine Conflict [22:52].
Listener Note: The interview with Sam Bendett and Jeff Edmonds was recorded on Tuesday, February 22 at 1 pm. At the time of recording, Russia had not yet launched a full-scale invasion of Ukraine. https://www.cna.org/news/AI-Podcast
Andy and Dave discuss the latest in AI news and research, including a report from the School of Public Health in Boston that shows why most "data for good" initiatives failed to impact the COVID-19 health crisis [0:45]. The Department of Homeland Security tests the use of robot dogs (from Ghost Robotics) for border patrol duties [5:00]. Researchers find that public trust in AI varies greatly depending on its application [7:52]. Researchers from Stanford University and Toyota Research Institute find extensive label and model errors in training data, such as over 70% of validation scenes (for publicly available autonomous vehicle datasets) containing at least one missing object box [12:05]. And principal researchers Josh Bongard and Mike Levin join Andy and Dave for more discussion on the latest Xenobots research [18:21].
Follow the link below to visit our website and explore the links mentioned in this episode.
https://www.cna.org/CAAI/audio-video
Andy and Dave discuss the latest in AI news and research, including the signing of the 2022 National Defense Authorization Act, which contains a number of provisions related to AI and emerging technology [0:57]. The Federal Trade Commission wants to tackle data privacy concerns and algorithmic discrimination and is considering a wide range of options to do so, including new rules and guidelines [4:50]. The European Commission proposes a set of measures to regulate digital labor platforms in the EU. Engineered Arts unveils Ameca, a gray-faced humanoid robot with "natural-looking" expressions and body movements [7:07]. And DARPA launches its AMIGOS project, aimed at automatically converting training manuals and videos into augmented reality environments [13:16]. In research, scientists at the Bar-Ilan University in Israel upend conventional wisdom on neural responses by demonstrating that the duration of the resting time (post-excitation) can exceed 20 milliseconds, that the resting period is sensitive to the origin of the input signal (e.g. left versus right), and that the neuron has a sharp transition from the refractory period to full responsiveness without an intermediate stutter phase [15:30]. Researchers at Victoria University use brain cells to play Pong using electric signals and demonstrate that the cells learn much faster than current neural networks, reaching the same point living systems reach after 10 or 15 rallies, vice 5000 rallies for computer-based AIs [19:37]. MIT researchers present evidence that ML is starting to look like human cognition, comparing various aspects of how neural networks and human brains accomplish their tasks [24:34]. And OpenAI creates GLIDE< a 3.5B parameter text-to-image generation model to generate even higher quality images than DALL-E, though it still has trouble with "highly unusual" scenarios [29:30]. The Santa Fe Institute publishes The Complex Alternative: Complexity Scientists on the COVID-19 Pandemic, 800 pages on how complexity interwove through the pandemic [33:50]. And Chris Peter has an algorithm to create a short movie after watching Hitchcock's Vertigo 20 times [35:22].
Please visit our website to explore the links mentioned in this episode.
https://www.cna.org/CAAI/audio-video
Andy and Dave welcome the hosts of the weekly podcast AI Today, Kathleen Walch and Ronald Schmelzer. On AI Today, Kathleen and Ron discuss topics related to how AI is making impacts around the globe, with a focus on having discussions with industry and business leaders to get their thoughts and perspectives on AI technologies, applications, and implementation challenges. Ron and Kathleen also co-founded Cognilytica, an AI research, education, and advisory firm. The four podcast hosts discuss a variety of topics, including the origins of the AI Today podcast, AI trends in industry and business, AI winters, and the importance of education.
https://www.cna.org/CAAI/audio-video
Andy and Dave discuss the latest in AI news and research, starting with the US Department of Defense creating a new position of the Chief Digital and AI Officer, subsuming the Joint AI Center, the Defense Digital Service, and the office of the Chief Data Officer [0:32]. Member states of UNESCO adopt the first-ever global agreement on the ethics of AI, which includes recommendations on protecting data, banning social scoring and mass surveillance, helping to monitor and evaluate, and protecting the environment [3:26]. The European Digital Rights and 119 civil society organizations launch a collective call for an AI Act to articulate fundamental rights (for humans) regarding AI technology and research [6:02]. The Future of Life Institute releases Slaughterbots 2.0: "if human: kill()" ahead of the 3rd session in Geneva of the Group of Governmental Experts discussing lethal autonomous weapons systems [7:15]. In research, Xenobots 3.0, the living robots made from frog cells, demonstrate the ability to replicate themselves kinematically, at least for a couple of generations (extended to four generations by using an evolutionary algorithm to model ideal structures for replication) [12:23]. And researchers from DeepMind, Oxford, and Sydney demonstrate the ability to collaborate with machine learning algorithms to discover new results in mathematics (in knot theory and representation theory); though another researcher attempts to dampen the utility of the claims. [17:57] And finally, Dr. Mike Stumborg joins Dave and Andy to discuss research in Human-Machine Teaming, why it's important, and where the research will be going [21:44].
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