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Breakthrough drug reverses skin aging and dramatically speeds healing

ABT-263 also increased the activity of genes involved in rebuilding damaged tissue. These included genes associated with collagen production and the formation of new blood vessels.

Collagen is a structural protein that provides strength and support to skin and other tissues. New blood vessel growth is equally important because healing tissue needs a steady supply of oxygen and nutrients as it rebuilds itself.

Together, these changes suggest that ABT-263 did more than simply remove damaged cells. The treatment also appeared to create conditions that helped aging skin mount a stronger regenerative response.

Video: Terminator dominates first human vs. robot cage match

On the plus side skynet might not decide to wipe humans out as it already knows it can kick the biological animal waste product out of them personally. Figuratively speaking. I think.

🖖😉🤝🤖🖖


We’ve seen some robot vs. robot cage matches, and those were pretty cool. Now we have what’s being billed as the first human vs. robot cage match, and it’s … pretty freaky?

We’ve all heard of how artificial intelligence and robots are going to take over the world and put everyone out of a job. That may include cage fighters if the technology on display here continues to improve. At a small private 100 person event in San Francisco on Friday September 18th, YouTuber Frankie LaPenna took on a six foot tall T-800 Terminator-style robot in a cage.

Xiaomi made an iPhone Duo. It’s Unhinged

Can the Xiaomi 18 Fold take on the iPhone Duo? 😅
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AI & the Threats & Dangers of Data Poisoning

Chuck Brooks is the president of Brooks Consulting International and one of Executive Mosaic’s GovCon Experts.

In my book Inside Cyber, I explored how artificial intelligence has evolved into the most potent weapon in an attacker’s arsenal as well as our most effective defensive tool. This dual nature is at the core of a significant change in security and privacy. The rate of change has only quickened since the book was released. We have advanced further into what I refer to as the Acceleration Era, in which AI systems, including large language models, or LLMs, improve quickly, incorporate into crucial processes and have a growing impact on business, governmental and societal decisions.

Data poisoning, or the intentional or unintentional contamination of the training data that forms these models, is one of the most pernicious new threats in this setting. Recent studies have highlighted LLMs’ continued vulnerability. A surprisingly small number of carefully constructed malicious documents, roughly a few hundred—can implant backdoors or change behavior in models with hundreds of millions to billions of parameters, according to studies, including collaborative work involving Anthropic, the UK AI Security Institute and the Alan Turing Institute. The amount of poisoned material does not have to increase in proportion to the size of the model or the amount of training data. The malicious samples’ absolute presence is what counts.

Alibaba Brags That Its Next-Gen Zhenwu V900 AI Chip Offers More On-Package Memory Than NVIDIA H200, Outlines Plans To Deploy 20 GW Of Compute, And Teases 4–10 trillion parameters For Upcoming Qwen Models

Alibaba is now claiming that the upcoming Zhenwu V900 chip will have 216GB of on-package memory, with an official launch slated for Q1 2027. We can only theorize that the V900 will leverage CXMT’s HBM3E solution, especially given their overlapping volume production timelines. The accelerator will sport chip-to-chip interconnect speeds of around 1.2 TB/s via Alibaba’s ICN Switch fabric, and offer around 3x the performance of Zhenwu M890, replete with native FP8/FP4 support. This means that each accelerator will offer a peak computing power of around 1.8 PFLOPS at FP16, given the ~0.6 PFLOPS that M890 had claimed to offer.

Critically, the ICN Switch can allow around 1,000 Zhenwu V900 chips to function as a single accelerator. However, Alibaba is now claiming that each V900 cluster can scale to 500,000 chips, entailing a whopping 108 petabyte of memory across the entire cluster! It remains to be seen if CXMT can fulfill the entirety of this oncoming demand.

Also, Alibaba is now offering its own bespoke rack-scale solution, replete with Yitian CPUs, Zhenwu V900 GPUs, ICN interconnect, Pangu NICs, and Zhenyue storage controllers.

Largest dataset of its kind could clarify how massive stars shaped early galaxies

The more astronomers learn about the universe’s earliest galaxies, the stranger they seem. Many of their surprising properties may be explained by differences between their massive stars and those in galaxies like our own Milky Way. A new University of Utah-led survey with the Hubble Space Telescope is shedding light on the stellar astrophysics operating in early galaxies.

The survey, called the Treasury of Extremely Metal-Poor O Stars (TEMPOS), uses ultraviolet (UV) observations from Hubble’s Cosmic Origins Spectrograph (COS) to study massive stars in nearby galaxies that are the best available analogs of stars in the early universe.

The unprecedentedly large dataset from TEMPOS could help astronomers build better models of massive stars to understand how they shaped galaxies when the universe was young. Such models are essential to interpret observations of early galaxies now coming from the James Webb Space Telescope, which launched in 2021.

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