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Tesla driver in fatal Texas crash pressed accelerator 100%, NTSB confirms

The National Transportation Safety Board (NTSB) said Wednesday that the driver of a Tesla who crashed into a house in June had pressed the accelerator pedal to 100%, overriding the company’s Full Self-Driving (Supervised) software.

Data recovered from the Tesla showed that the vehicle was traveling more than 70 miles per hour when it struck a house in Katy, Texas, killing 76-year-old resident Martha Avila, according to the NTSB. The family of the victim has since sued the alleged driver, 44-year-old Michael Butler, and Tesla, claiming negligence. Butler has also been charged with manslaughter.

The safety board shared the information as part of a preliminary report on the progress of its investigation into the crash. The National Highway Traffic Safety Administration is also probing the incident.

The data confirms Tesla’s account of the crash, which the company shared in the days after it happened in order to show that its advanced driver assistance system wasn’t to blame. “[T]his [allegation] makes no sense. FSD drives slowly through neighborhood streets and this was a high speed crash!” Tesla CEO Elon Musk wrote on X shortly after the crash.

The NTSB said Wednesday that the 44-year-old driver was using Full Self-Driving (Supervised) on Rose Hollow Lane, a residential two-lane road with a speed limit of 30 miles per hour, prior to the crash. Security camera footage obtained by the safety board showed the car accelerating through an intersection, leaving the road, and hitting the house. The “weather was clear, the roadway was dry, and daylight conditions were present,” according to the NTSB.

Tesla requires that drivers using Full Self-Driving (Supervised) pay attention to the road and be ready to take control at any moment. Butler allegedly told authorities that he had “passed out” and that he was using Tesla’s driver assistance system. Police reportedly discovered that his Google searches included the terms “Tesla FSD not aggressive enough 2026,” “Tesla not aggressive enough,” and “Tesla FSD too timid,” according to local ABC news affiliate station KTRK TV.

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Inside Ode with Anthropic, the startup betting AI services are the future of enterprise

Can a handful of engineers really do the work of an army of consultants? That’s the bet behind Ode with Anthropic — the joint venture dedicated to embedding forward-deployed engineers in enterprise firms, backed by Anthropic, Blackstone, Hellman & Friedman, Goldman Sachs and others.  

On this episode of TechCrunch’s Equity podcast, Rebecca Bellan sits down with Ode’s leaders Chris Taylor and Eddie Siegel, who founded Fractional AI, the applied AI services startup that Ode acquired earlier this year to serve as the new venture’s core. The three discuss why so many enterprise AI pilots never make it to production and why they think AI-native services are about to become one of the biggest categories in tech. 

Subscribe to Equity on YouTube, Apple Podcasts, Overcast, Spotify and all the casts. You also can follow Equity on X and Threads, at @EquityPod. 


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Microsoft patches record number of security vulnerabilities, citing its use of AI

Microsoft released a record number of security patches for Windows, Office, and other tech product lines this week, citing the use of AI to aid the discovery of code vulnerabilities.

The technology and cloud giant issued patches for 570 security flaws on Tuesday as part of its monthly scheduled release of fixes, which security researchers have long dubbed “Patch Tuesday.”

At least two of the vulnerabilities are classified as zero-days, meaning that they were exploited before Microsoft was made aware of them. One bug affecting Windows Server allows hackers to escalate their privileges from a limited user to a system administrator. Another bug affects the SharePoint file sharing server — the U.S. government’s cybersecurity agency CISA has warned hackers were actively exploiting the bug to compromise organizations.

Krebs on Security first reported the news.

The huge patch update comes a week after Microsoft said in a blog post that it expected its usual batch of monthly security patches to be far higher in number than before. The company cited its use of AI to help its employees uncover previously undiscovered security bugs in its software.

“As AI helps defenders discover more issues, customers will see a higher volume of security updates included in each security release,” said Windows boss Pavan Davuluri.

As AI models become more advanced and focused on cybersecurity issues, security researchers are using them to uncover vulnerabilities that may have been dormant in software code for years, if not longer. Parts of Microsoft’s Windows code dates back decades.

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Whatnot acquires Shaped to power real-time live shopping recommendations

Livestream shopping app Whatnot announced Wednesday that it has acquired Shaped, a machine learning company that specializes in real-time recommendation and search systems. The deal is meant to strengthen Whatnot’s discovery and personalization capabilities as the platform continues to expand across new product categories and millions of buyers.

According to the company, the acquisition helps Whatnot continue its investment in AI as it looks to solve one of live commerce’s biggest challenges: helping shoppers find the right products while inventory, auctions, and buyer demand change in real time. 

Unlike traditional e-commerce platforms, where product catalogs remain relatively stable, Whatnot’s marketplace is constantly evolving, and live auctions can end within minutes or last for hours.

“By combining Shaped’s technology with Whatnot’s existing systems, we can make recommendations faster, more responsive, and more personalized,” Emmanuel Fuentes, VP of Data and AI at Whatnot, told TechCrunch. “That speed matters because live commerce is a uniquely hard recommendation problem. Inventory changes by the second, shows start and end continuously, and buyer intent shifts throughout a show.”

Fuentes said the company has spent the last six years improving the speed of its recommendation engine, reducing recommendation latency from roughly a day to just minutes. Integrating Shaped’s technology is expected to push those recommendations even closer to real time. The company says its systems process more than 500,000 hours of live video and millions of real-time interactions every week, using that data to continuously improve recommendations.

Founded to help businesses build AI-powered recommendation systems, Shaped developed technology that combines existing customer data with large language models and machine learning to deliver highly personalized search and discovery experiences. Its customer roster included companies such as Outdoorsy and QVC.

As part of the acquisition, Shaped founder and CEO Tullie Murrell, along with nearly a dozen engineers and AI researchers, will join Whatnot. Murrell will lead the company’s newly formed Applied AI Research group. (Notably, Murrell worked at Meta before launching Shaped.)

The acquisition comes as Whatnot experiences significant growth. Launched in 2019, the company recently revealed that sellers have surpassed 1 billion orders. Last year, Whatnot raised $225 million in Series F funding, giving the company a valuation of more than $11 billion after adding 20 million buyers over the past year.

Whatnot has also significantly broadened its marketplace, launching more than 35 new categories last year — including art, golf, and vinyl — and more than 45 additional categories during the first half of 2026, with new subcategories continuing to roll out each month.

Additionally, the move comes as resale giants race to integrate AI throughout their platforms, such as eBay and Poshmark

This story has been updated to correct dates that incorrectly referred to the first half of 2025. The correct time period is the first half of 2026

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