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Our smart devices take voice commands from us, check our heartbeats, track our sleep, translate text, send us reminders, capture photos and movies, and let us talk to family and friends continents away.

Now imagine turbocharging those capabilities. Holding in-depth, natural language exchanges on academic or personal queries; running our vital signs through a global database to check on imminent health issues; packing massive databases to provide comprehensive real-time translation among two or more parties speaking different languages; and conversing with GPS software providing details on the best burgers, movies, hotels or people-watching spots trending along your route.

Tapping into the seductive power of large language models and natural language processing, we’ve witnessed tremendous progress in communications between us and technology that we increasingly rely on in our daily lives.

The integration of mechanical memory in the form of springs has for hundreds of years proven to be a key enabling technology for mechanical devices (such as clocks), achieving advanced functionality through complex autonomous movements. Currently, the integration of springs in silicon-based microtechnology has opened the world of planar mass-producible mechatronic devices from which we all benefit, via air-bag sensors for example.

For a of minimally and even non-invasive biomedical applications however, that can safely interact mechanically with cells must be achieved at much smaller scales (10 microns) and with much softer forces (pico Newton scale, i.e., lifting weights less than one millionth of a mg) and in customized three-dimensional shapes.

Researchers at the Chemnitz University of Technology, the Shenzhen Institute of Advanced Technology of the Chinese Academy of Sciences and the Leibniz IFW Dresden, in a recent publication in Nature Nanotechnology, have demonstrated that controllable springs can be integrated at arbitrary chosen locations within soft three-dimensional structures using confocal photolithographic manufacturing (with nanoscale precision) of a novel magnetically active material in the form of a photoresist impregnated with customizable densities of magnetic nanoparticles.

Scientists have grown a tiny brain-like organoid out of human stem cells, hooked it up to a computer, and demonstrated its potential as a kind of organic machine learning chip, showing it can quickly pick up speech recognition and math predictions.


Clusters of brain cells grown in the lab have shown potential as a new type of hybrid bio-computer.

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A new report by Computer scientists from the National Institute of Standards and Technology presents new kinds of cyberattacks that can “poison” AI systems.

AI systems are being integrated into more and more aspects of our lives, from driving vehicles to helping doctors diagnose illnesses to interacting with customers as online chatbots. To perform these tasks the models are trained on vast amounts of data, which in turn helps the AI predict how to respond in a given situation.

This morning in breaking news, Brett Adcock CEO of Figure Robotics, dropped a mind-blowing demo showing that their Figure 1 robot can now do end-to-end AI training. This demo of the bot now able to make coffee is just one of many applications that they are promising the bot can do. Robotics expert Dr. Scott Walter does a comparison with Tesla Bot and Google’s Mobile ALOHA Scott Walter is an Aerospace Engineer with a Ph.D. in Mechanical Engineering and has co-founded two robotics companies Follow Scott on X @GoingBallistic5 Get Free TESLA Milestone Tables M.

Eli Lilly & Novartis are entering a strategic research collaboration with Isomorphic Labs to use state-of-the-art AI technologies—including the next-gen model of #AlphaFold—to discover novel small molecule therapeutics for select biological targets.


We are reimagining the entire drug discovery process from first principles with an AI-first approach.