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Grok in Tesla’s Leaked / Tesla Expands Robotaxi Invites / Surprising EV Sales Data

Questions to inspire discussion.

🏭 Q: How much LFP cell production capacity does Tesla have in Nevada? A: Tesla’s Nevada facility has equipment for 7–8 GWh of LFP cell production across two production lines, potentially for EVe and grid storage cells.

Tesla Business and Sales.

📊 Q: What are the expectations for Tesla’s Q2 PND report? A: Troy Teslike estimates 356,000 deliveries, while analyst consensus is 385,000, but PND reports are becoming less significant for Tesla’s business model.

💰 Q: What’s crucial for Tesla to become a multi-trillion dollar company? A: Unsupervised FSD rollout and Optimus sales at scale are key, not just increased car or megapack sales.

🇨🇳 Q: How are Tesla’s China sales performing? A: Latest week sales were 20,684 units, down 4.9% QoQ and 11% YoY, but year-to-date figures show Tesla China is closing the gap, down only 4.6% YoY.

Will AI need a body to come close to human-like intelligence?

The first robot I remember is Rosie from The Jetsons, soon followed by the urbane C-3PO and his faithful sidekick R2-D2 in The Empire Strikes Back. But my first disembodied AI was Joshua, the computer in WarGames who tried to start a nuclear war – until it learned about mutually assured destruction and chose to play chess instead.

At age seven, this changed me. Could a machine understand ethics? Emotion? Humanity? Did artificial intelligence need a body? These fascinations deepened as the complexity of non-human intelligence did with characters like the android Bishop in Aliens, Data in Star Trek: TNG, and more recently with Samantha in Her, or Ava in Ex Machina.

But these aren’t just speculative questions anymore. Roboticists today are wrestling with the question of whether artificial intelligence needs a body? And if so, what kind?

New AI system uncovers hidden cell subtypes, boosts precision medicine

In this view of cHL (classic Hodgkin Lymphoma) tissue, CellLENS identified subtle but distinct CD4 T cell subpopulations infiltrating a tumor, lingering at tumor boundaries, and found at a distance from tumors. CellLENS enables the potential precision therapy strategies against specific immune cell populations in the tissue environment.

Image courtesy of the researchers.

RisingAttacK: New technique can make AI ‘see’ whatever you want

Researchers have demonstrated a new way of attacking artificial intelligence computer vision systems, allowing them to control what the AI “sees.” The research shows that the new technique, called RisingAttacK, is effective at manipulating all of the most widely used AI computer vision systems.

At issue are so-called “adversarial attacks,” in which someone manipulates the data being fed into an AI system to control what the system sees, or does not see, in an image. For example, someone might manipulate an AI’s ability to detect , pedestrians or other cars—which would cause problems for . Or a hacker could install code on an X-ray machine that causes an AI system to make inaccurate diagnoses.

“We wanted to find an effective way of hacking AI vision systems because these vision systems are often used in contexts that can affect human health and safety—from autonomous vehicles to health technologies to ,” says Tianfu Wu, co-corresponding author of a paper on the work and an associate professor of electrical and computer engineering at North Carolina State University.

Tesla’s JUICY New Impact Report (highlights in 10 mins!)

Tesla’s 2024 impact report highlights the company’s progress in accelerating its mission to sustainable energy through innovative technologies, including autonomy, AI, and reduced emissions, with a focus on expanding its ecosystem and making sustainable transportation and energy solutions more accessible ## ## Questions to inspire discussion.

Sustainable Transportation.

🚗 Q: How will Tesla’s robo taxi network impact transportation?

A: Tesla’s autopilot-powered robo taxi network will be far safer than human drivers, lower emissions, and increase accessibility of sustainable transportation, improving city sustainability and accelerating Tesla’s mission.

🏙️ Q: What are the benefits of Tesla vehicles compared to other options?

A: Tesla vehicles offer premium features rivaling luxury cars while maintaining a total cost of ownership comparable to mass market vehicles, providing significantly more value at a similar price point.

Tiny light-sensitive magnetic robots can clear up bacterial infections in sinuses

Tiny magnetic bots that are activated by light can clear bacterial infections deep in the sinus cavities, then be expelled by blowing out the nose.

A new study published in Science Robotics unveiled copper single–atom–doped bismuth oxoiodide microbots, each smaller than a grain of salt, that can be tracked and guided to the location of infection via X-ray imaging, thus providing a precise, minimally invasive therapeutic strategy for managing clinically.

Sinusitis is a common respiratory condition often linked to biofilm produced by bacteria like Streptococcus pyogenes. This condition causes inflammation of the sinus lining and leads to symptoms such as , reduced sense of smell, facial pain, and, in some dire cases, even memory impairment.

Mathematical approach makes uncertainty in AI quantifiable

How reliable is artificial intelligence, really? An interdisciplinary research team at TU Wien has developed a method that allows for the exact calculation of how reliably a neural network operates within a defined input domain. In other words: It is now possible to mathematically guarantee that certain types of errors will not occur—a crucial step forward for the safe use of AI in sensitive applications.

From smartphones to self-driving cars, AI systems have become an everyday part of our lives. But in applications where safety is critical, one central question arises: Can we guarantee that an AI system won’t make serious mistakes—even when its input varies slightly?

A team from TU Wien—Dr. Andrey Kofnov, Dr. Daniel Kapla, Prof. Efstathia Bura and Prof. Ezio Bartocci—bringing together experts from mathematics, statistics and computer science, has now found a way to analyze neural networks, the brains of AI systems, in such a way that the possible range of outputs can be exactly determined for a given input range—and specific errors can be ruled out with certainty.