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Category: robotics/AI

Elon Announces MOST Powerful FSD Update Ever

Questions to inspire discussion.

đŸ›Łïž Q: What specific improvements can we expect from the new FSD model? A: The new model will see and avoid potholes, drive better in parking lots, find parking spaces more efficiently, figure out pickup and drop-off zones for robotaxis, and handle high chaos situations like crowded areas more effectively.

Safety and Regulations.

🚩 Q: How does FSD’s safety compare to human drivers? A: Tesla’s FSD technology is already much safer than humans with the current Version 4, which has 8 cameras and 10x better parameters than previous versions, and it’s expected to improve further with future updates.

📊 Q: How significant are the improvements in the new FSD model? A: While the model has 10x better parameters, the features may not be 10x better, but improvements could be greater than 10x due to hard-to-measure benefits like reduced driving stress and increased safety.

đŸš« Q: What’s limiting FSD’s full potential? A: Regulations currently hold FSD back from reaching its full potential, despite its ability to drive faster and handle high chaos situations more effectively.

Continue reading “Elon Announces MOST Powerful FSD Update Ever” | >

Programmable Soft Materials: A Leap Forward in Energy Absorption and Shape-Shifting Design

Researchers from Lawrence Livermore National Laboratory (LLNL), in collaboration with Harvard University, Caltech, Sandia National Laboratories, and Oregon State University, have unveiled a groundbreaking innovation in materials science: a programmable soft material capable of bending, bouncing, and absorbing energy on demand. This new material, described in the journal Advanced Materials, could pave the way for next-generation protective gear, aerospace structures, and adaptive robotic systems.

👉 Read the original article on Phys.org

OpenAI releases ChatGPT-5 as AI race accelerates

OpenAI released a keenly awaited new generation of its hallmark ChatGPT on Thursday, touting “significant” advancements in artificial intelligence capabilities as a global race over the technology accelerates.

ChatGPT-5 is rolling out free to all users of the AI tool, which is used by nearly 700 million people weekly, OpenAI said in a briefing with journalists.

Co-founder and chief executive Sam Altman touted this latest iteration as “clearly a model that is generally intelligent.”

AI accelerates development of advanced heat-dissipating polymers

A machine learning method developed by researchers from the Institute of Science Tokyo, the Institute of Statistical Mathematics, and other institutions accurately predicts liquid crystallinity of polymers with 96% accuracy. They screened over 115,000 polyimides and selected six candidates with a high probability of exhibiting liquid crystallinity. Upon successful synthesis and experimental analyses, these liquid crystalline polyimides demonstrated thermal conductivities up to 1.26 W m⁻Âč K⁻Âč, accelerating the discovery of efficient thermal materials for next-generation electronics.

Finding new polymer materials that can efficiently dissipate heat while maintaining high reliability is one of the biggest challenges in modern electronics. One promising solution is liquid crystalline polyimides, a special class of polymers whose molecules naturally align into highly ordered structures.

These ordered chains create pathways for heat flow, making liquid crystalline polyimides highly attractive for thermal management in semiconductors, flexible displays, and next-generation devices. However, designing these polymers has long relied on trial and error because researchers lacked clear design rules to predict whether a polymer would form a liquid crystalline phase.

PCI-SIG Announces PCI-Express Gen 8 Specification: 256 Gbps Per Lane Per Direction, Arrives 2028

PCI-SIG today announced the PCI Express (PCIe) 8.0 specification will double the data of the PCIe 7.0 specification to 256.0 GT/s and is planned for release to members by 2028. “Following this year’s release of the PCIe 7.0 specification, PCI-SIG is excited to announce that the PCIe 8.0 specification will double the data rate to 256 GT/s, maintaining our tradition of doubling bandwidth every three years to support next-generation applications,” said Al Yanes, PCI-SIG President and Chairperson. “With the increasing data throughput required in AI and other applications, there remains a strong demand for high performance. PCIe technology will continue to deliver a cost-effective, high-bandwidth, and low-latency I/O interconnect to meet industry needs.”

AI-Powered Discovery of High-Performance Polymers for Heat Dissipation

In a groundbreaking step forward for polymer science and electronics cooling technology, researchers from Japan have leveraged artificial intelligence to identify a new class of liquid crystalline polyimides with remarkably high thermal conductivity. Their work, recently published in npj Computational Materials, combines data science, chemistry, and machine learning to accelerate the search for next-generation materials capable of efficiently dissipating heat in compact, high-performance electronics.

🔗 Original article on Phys.org

CRISPR-GPT Turns Novice Scientists into Gene Editing Experts

CRISPR technology has revolutionized biology, largely because of its simplicity compared to previous gene editing techniques. However, it still takes weeks to learn, design, perform, and analyze CRISPR experiments; first-time CRISPR users often end up with low editing efficiencies and even experts can make costly mistakes.

In a new study, researchers from Stanford University, Princeton University, and the University of California, Berkeley, teamed up with Google DeepMind to create CRISPR-GPT, an artificial intelligence (AI) tool that can guide researchers through every aspect of CRISPR editing from start to finish in as little as one day.1 The results, published in Nature Biomedical Engineering, demonstrate that researchers with no previous CRISPR experience could achieve up to 90 percent efficiency in their first shot at gene editing using the tool.

CRISPR-GPT is a large language model (LLM), a type of AI model that uses text-based input data. Led by Le Cong of Stanford University and Mengdi Wang of Princeton University, the team trained the model on over a decade of expert discussions, as well as established protocols and peer-reviewed literature. They designed it to cover gene knockout, base editing, prime editing, and epigenetic editing systems, and benchmarked the tool against almost 300 test questions and answers.

High-level visual representations in the human brain are aligned with large language models

Doerig, Kietzmann and colleagues show that the brain’s response to visual scenes can be modelled using language-based AI representations. By linking brain activity to caption-based embeddings from large language models, the study reveals a way to quantify complex visual understanding.

Anthropic says they’ve found a new way to stop AI from turning evil

AI is a relatively new tool, and despite its rapid deployment in nearly every aspect of our lives, researchers are still trying to figure out how its “personality traits” arise and how to control them. Large learning models (LLMs) use chatbots or “assistants” to interface with users, and some of these assistants have exhibited troubling behaviors recently, like praising evil dictators, using blackmail or displaying sycophantic behaviors with users. Considering how much these LLMs have already been integrated into our society, it is no surprise that researchers are trying to find ways to weed out undesirable behaviors.

Anthropic, the AI company and creator of the LLM Claude, recently released a paper on the arXiv preprint server discussing their new approach to reining in these undesirable traits in LLMs. In their method, they identify patterns of activity within an AI model’s neural network—referred to as “persona vectors”—that control its character traits. Anthropic says these persona vectors are somewhat analogous to parts of the brain that “light up” when a person experiences a certain feeling or does a particular activity.

Anthropic’s researchers used two open-source LLMs, Qwen 2.5-7B-Instruct and Llama-3.1-8B-Instruct, to test whether they could remove or manipulate these persona vectors to control the behaviors of the LLMs. Their study focuses on three traits: evil, sycophancy and hallucination (the LLM’s propensity to make up information). Traits must be given a name and an explicit description for the vectors to be properly identified.

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