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Category: robotics/AI – Page 4

Machine learning for materials discovery and optimization

This Collection supports and amplifies research related to SDG 9 — Industry, Innovation & Infrastructure.

Discovering new materials with customizable and optimized properties, driven either by specific application needs or by fundamental scientific interest, is a primary goal of materials science. Conventionally, the search for new materials is a lengthy and expensive manual process, frequently based on trial and error, requiring the synthesis and characterization of many compositions before a desired material can be found. In recent years this process has been greatly improved by a combination of artificial intelligence and high-throughput approaches. Advances in machine learning for materials science, data-driven materials prediction, autonomous synthesis and characterization, and data-guided high-throughput exploration, can now significantly accelerate materials discovery.

This Collection brings together the latest computational and experimental advances in artificial intelligence, machine learning and data-driven approaches to accelerate high-throughput prediction, synthesis, characterization, optimization, discovery, and understanding of new materials.

Defeating Nondeterminism in LLM Inference

Reproducibility is a bedrock of scientific progress. However, it’s remarkably difficult to get reproducible results out of large language models.

For example, you might observe that asking ChatGPT the same question multiple times provides different results. This by itself is not surprising, since getting a result from a language model involves “sampling”, a process that converts the language model’s output into a probability distribution and probabilistically selects a token.

What might be more surprising is that even when we adjust the temperature down to 0This means that the LLM always chooses the highest probability token, which is called greedy sampling. (thus making the sampling theoretically deterministic), LLM APIs are still not deterministic in practice (see past discussions here, here, or here). Even when running inference on your own hardware with an OSS inference library like vLLM or SGLang, sampling still isn’t deterministic (see here or here).

Mo Gawdat on AI, ethics & machine mastery: How Artificial Intelligence will rule the world

Mo Gawdat warns that AI will soon surpass human intelligence, fundamentally changing society, but also believes that with collective action, ethical development, and altruistic leadership, humans can ensure a beneficial future and potentially avoid losing control to AI

## Questions to inspire discussion.

AI’s Impact on Humanity.

🤖 Q: How soon will AI surpass human intelligence? A: According to Mo Gawdat, AI will reach AGI by 2026, with intelligence measured in thousands compared to humans, making human intelligence irrelevant within 3 years.

🌍 Q: What potential benefits could AI bring to global issues? A: 12% of world military spending redirected to AI could solve world hunger, provide universal healthcare, and end extreme poverty, creating a potential utopia.

Preparing for an AI-Driven Future.

Continue reading “Mo Gawdat on AI, ethics & machine mastery: How Artificial Intelligence will rule the world” | >

US Energy Secretary’s INSANE Bet Against Elon Musk

Questions to inspire discussion.

Energy for AI and Infrastructure.

🤖 Q: How does AI development impact energy demands? A: AI development will drive massive demand for electricity, with solar and batteries being the only energy source with an unbounded upper limit to scale and meet these demands.

⛽ Q: Can solar energy support existing infrastructure? A: Solar energy can produce synthetic biofuels and oil and gas through chemical processes, enabling it to power existing infrastructure that runs on traditional fuels.

Expert Predictions.

🚗 Q: What does Elon Musk predict about future energy sources? A: Elon Musk predicts that solar and batteries will dominate the future energy landscape, citing China’s massive investment as a key factor in this prediction.

Continue reading “US Energy Secretary’s INSANE Bet Against Elon Musk” | >

AI system leverages standard security cameras to detect fires in seconds

Fire kills nearly 3,700 Americans annually and destroys $23 billion in property, with many deaths occurring because traditional smoke detectors fail to alert occupants in time.

Now, the NYU Fire Research Group at NYU Tandon School of Engineering has developed an artificial intelligence system that could significantly improve by detecting fires and smoke in using ordinary security cameras already installed in many buildings.

Published in the IEEE Internet of Things, the research demonstrates a system that can analyze and identify fires within 0.016 seconds per frame—faster than the blink of an eye—potentially providing crucial extra minutes for evacuation and . Unlike conventional smoke detectors that require significant smoke buildup and proximity to activate, this AI system can spot fires in their earliest stages from video alone.

Elon Musk: Robotaxis Will Replace Personal Cars, Not Just Uber

Questions to inspire discussion.

🧠 Q: How does Tesla’s upcoming AI chip compare to the current one? A: Tesla’s AI5 chip will be 40 times better than the current AI4 chip, which is already capable of achieving self-driving safety at least 2–3 times that of a human.

💰 Q: What is the expected pricing for Tesla’s robotaxi service? A: Tesla’s robotaxi service is projected to cost $2 per mile at launch, which is cheaper than Uber rides in high-cost areas like Seattle.

Impact on Transportation.

🚘 Q: How will robotaxis affect car ownership? A: Robotaxis are expected to become a viable alternative to car ownership, especially when prices reach $1 per mile, making them cheaper than options like airport parking.

💼 Q: How does Tesla’s robotaxi cost compare to competitors? A: Tesla’s robotaxi can be built and deployed for half the cost of competitors like Whim, potentially offering more competitive pricing.

Continue reading “Elon Musk: Robotaxis Will Replace Personal Cars, Not Just Uber” | >
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