James Douma Explains the Challenge and Benefits of Tesla’s End to End Neural Network Self Driving

Businesses want a 100% complete AI systems that can be trained directly with just data. This is what OpenAI was able to do with ChatGPT and large language models. This is what Tesla has been able to achieve with version 12 of FSD (Full self driving). The Tesla FSD v12 was demonstrated for nearly one …

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Researchers Accurately Simulate 100 Million Atoms With Machine Learning

Harvard researchers bring the accuracy, sample efficiency, and robustness of deep equivariant neural networks to the simulate 44 million atoms. This is achieved through a combination of innovative model architecture, massive parallelization, and models and implementations optimized for efficient GPU utilization. The resulting Allegro architecture bridges the accuracy speed tradeoff of atomistic simulations and enables …

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AI and Programming Legend Stephen Wolfram Talks ChatGPT and the Future

Stephen Wolfram made WolframAlpha which is the main online program for math and physics solutions. He has made one of the first plugins for ChatGPT. He starts by explaining that ChatGPT and the large language models is able to generate human-like text and responses based upon extremely good statistical productions of the next word in …

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Elon Musk Says Tesla FSD Version 11 This Week or Next

Elon Musk says Tesla FSD version 11 should start rolling out later this week, next week at the latest. Tesla is starting to make use of neural nets for vehicle navigation & control, not just vision. Wen fsd beta v11.3? — Tesla Owners Silicon Valley (@teslaownersSV) January 14, 2023 Should start rolling out later this …

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Neural Network Transformers Explained and Why Tesla FSD has an Unbeatable Lead

Dr. Know-it-all Knows it all explains how Neural Network Transformers work. Neural Network Transformers were first created in 2017. He explains how Transformers remember data better than other neural network architectures. Neural Network Transformers are the basis for Tesla FSD. Neural Network Transformers continually improve with more and more data. Tesla FSD now has over …

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Google AI Architecture Pathways Can Learn Millions of Things

The Google Research next-generation AI architecture is called Pathways. It will enable a single model to learn millions of things instead of just one thing. This will be a massive phase change and up leveling of neural network and AI capabilities. Pathways is part of the improvements Google is making to their AI. Google new …

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Elon Musk Interviewed by Lex Friedman on Mars, Tesla FSD and Teslabot

Elon Musk had a 2.5 hour interview with Lex Friedman where he talked SpaceX Starship, Mars, Tesla FSD and Teslabot. Elon Musk is back to being confident that the Raptor 2 mass production problems will be overcome. There are a lot of unique materials in the Raptor. They created new alloys. It is also a …

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What Does It Mean to a Researcher at Deep Mind #emtechdigital

David Budden is a Research Engineering Team Lead, DeepMind. He will discuss Engineering Intelligence. David talked about how innovation can come from anywhere in the company. A Deep Fake (fake picture) project was performed by an intern. It is a myth that deep mind does not open source. Starcraft can take a long time and …

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Airbus CTO Predicts a Quantum Computing Era in Aerospace

Airbus chief technology officer (CTO) Grazia Vittadini predicts a quantum era in aerospace. Vittadini made this prediction in a Wall Street Journal article. Quantum computing research is being applied to tough flight physics problems. This is even with the small quantum computer systems that are available today. Nextbigfuture believes the pre-error corrected quantum computers that …

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IBM overcomes von Neumann bottleneck for AI hundreds of time faster using hundreds of times less energy

IBM Research AI team demonstrated deep neural network (DNN) training with large arrays of analog memory devices at the same accuracy as a Graphical Processing Unit (GPU)-based system. This is a major step on the path to the kind of hardware accelerators necessary for the next AI breakthroughs. Why? Because delivering the Future of AI …

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