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Category: robotics/AI – Page 134

DNA-based neural network learns from examples to solve problems

Neural networks are computing systems designed to mimic both the structure and function of the human brain. Caltech researchers have been developing a neural network made out of strands of DNA instead of electronic parts that carries out computation through chemical reactions rather than digital signals.

An important property of any neural network is the ability to learn by taking in information and retaining it for future decisions. Now, researchers in the laboratory of Lulu Qian, professor of bioengineering, have created a DNA-based neural network that can learn. The work represents a first step toward demonstrating more complex learning behaviors in .

A paper describing the research appears in the journal Nature on September 3. Kevin Cherry, Ph.D., is the study’s first author.

A robot learns to handle bulky objects like humans do after just one lesson

For all their technological brilliance, from navigating distant planets to performing complex surgery, robots still struggle with a few basic human tasks. One of the most significant challenges is dexterity, which refers to the ability to grasp, hold and manipulate objects. Until now, that is. Scientists from the Toyota Research Institute in Massachusetts have trained a robot to use its entire body to handle large objects, much like humans do.

Tesla’s Robotaxi Strategy EXPLAINED

Questions to inspire discussion.

Business Strategy and Market Impact.

💼 Q: How is Tesla positioning its robo taxi service in the market? A: Tesla is aiming to change the world towards sustainable transport, winning the first two-month race in deployment, service area, and metrics, rather than engaging in an “online dork battle” about robo taxis.

📊 Q: What’s Tesla’s approach to incidents in its robo taxi service? A: Tesla is carefully managing the launch to minimize the impact of incidents on reaching peak gross margin and revenue, prioritizing this over the cost of safety monitors.

FSD Supervised in Australia.

🦘 Q: How successful is Tesla’s FSD Supervised rollout in Australia? A: It’s considered a success story, with 8 cameras processing live information, navigating complex environments like Brisbane’s “spaghetti bowl” of ramps and exits, and handling roundabouts and highway merges.

Continue reading “Tesla’s Robotaxi Strategy EXPLAINED” | >

Shadow AI Discovery: A Critical Part of Enterprise AI Governance

MITs State of AI in Business report revealed that while 40% of organizations have purchased enterprise LLM subscriptions, over 90% of employees are actively using AI tools in their daily work. Similarly, research from Harmonic Security found that 45.4% of sensitive AI interactions are coming from personal email accounts, where employees are bypassing corporate controls entirely.

This has, understandably, led to plenty of concerns around a growing “Shadow AI Economy”. But what does that mean and how can security and AI governance teams overcome these challenges?

Contact Harmonic Security to learn more about Shadow AI discovery and enforcing your AI usage policy.

Tesla Is Planning Something Massive

Questions to inspire discussion.

🗓️ Q: When will more details about Tesla’s master plan part 4 be revealed? A: Elon Musk will add specifics to the master plan part 4 at the upcoming annual shareholder meeting on November 6th, including key milestones for achieving sustainable abundance.

AI and Manufacturing.

🧠 Q: What is Elon Musk’s focus regarding AI development? A: Musk is prioritizing the development of AI compute capacity and deep learning models, as evidenced by his focus on XAI and Grock 5, to drive innovation in Tesla’s products and services.

🏭 Q: How does Tesla plan to improve its manufacturing processes? A: Tesla aims to create a custom AI solution using Grock agents to develop a cybernetic organism capable of manufacturing humanoids more efficiently than current Tesla methods.

🤖 Q: What is the potential timeline for Grock 5 to achieve AGI? A: Elon Musk believes Grock 5 has a chance to become AGI (Artificial General Intelligence) by next year, potentially allowing Tesla to achieve supremacy in manufacturing through superior AI.

Continue reading “Tesla Is Planning Something Massive” | >

New AI model predicts which genetic mutations truly drive disease

Scientists at Mount Sinai have created an artificial intelligence system that can predict how likely rare genetic mutations are to actually cause disease. By combining machine learning with millions of electronic health records and routine lab tests like cholesterol or kidney function, the system produces “ML penetrance” scores that place genetic risk on a spectrum rather than a simple yes/no. Some variants once thought dangerous showed little real-world impact, while others previously labeled uncertain revealed strong disease links.

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