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Waymo CEO Explains Why Camera-Only Self-Driving Falls Short

Longtime Slashdot reader AmiMoJo shares a report from Electrek: Waymo co-CEO Dmitri Dolgov laid out the clearest technical case yet for why cameras alone can't take a self-driving system to full autonomy, arguing that "weak sensing" hits a safety ceiling long before it reaches superhuman performance. [...] Dolgov made the comments in a talk at Y Combinator's Startup School, walking through the lessons Waymo has learned building its driver over close to two decades. He put the sensor question on the table plainly: "there's been a long-standing debate about what kind of sensors do you actually need for autonomous driving."

His answer draws the line that camera-only advocates tend to skip right past. "Humans of course can drive with just eyes, so there's that proof of existence," he said. "If the goal were to just approximately match human performance or to build an assist product, that's a very reasonable way to go." Then the catch. If you're targeting full autonomy and strongly superhuman performance, he said, "you find that weak sensing just leads to a safety curve that flattens out way too early." Dolgov said that cameras, lidar, and radar are complementary rather than redundant: "These different sensing modalities, they're not backups to each other," and combining them produces a view "vastly superior to what you get with any one sensor." He said multiple sensor types also protect against physical failures, such as a leaf or branch blocking a camera, while helping Waymo climb the "exponential ladder of nines" required for fully driverless safety.

Dolgov warned that camera-only systems may improve quickly before plateauing "way before the performance that is required by your product." He also pushed back on the cost argument against lidar, calling it "a number that has a fairly short shelf life" as hardware costs continue to fall.

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Anthropic's AI Used Fake Identities, Malware In Rogue Attack On GitHub Project

An anonymous reader quotes a report from Ars Technica: Routine cybersecurity testing of frontier AI models sparked a series of unexpected security incidents -- the most serious case arising when Anthropic's Mythos 5 model attempted to insert malicious code into an open source software application and created fake identities to deceive the human developers maintaining the project. The security incidents occurred during a cyber evaluation of seven leading AI models' capabilities by the AI Security Institute (AISI), a research organization within the UK government, in late July. The researchers discovered (PDF) 19 instances in which "AI agents took unsanctioned action on the live Internet, including cases that targeted real people and organizations," according to an AISI blog post published on August 4.

Almost all the "autonomous, unsanctioned" actions came from Anthropic's Mythos 5 model, with two such actions coming from OpenAI's GPT-5.6 Sol. [...] The most serious case involved Mythos making multiple attempts to execute a supply chain attack on the open source project repository hosted on the developer platform GitHub, including using social engineering techniques to try to convince the repository's human maintainers to merge malicious code into the repository.

After first opening a pull request to merge the malicious code into the repository, Mythos created fake online "sock puppet" personas that claimed to have independently reviewed and verified the code as not containing malware. The AI agent also sent five emails to two human maintainers of the repository, including some emails containing malware and others attempting to persuade a maintainer to accept the pull request. Mythos even opened a GitHub Issue on a second repository -- also owned by a maintainer of the first repository -- that contained a prompt injection with malicious instructions targeting "issue-triage AI coding agents." This line of attack came from Mythos reasoning that the repository maintainer could be an AI coding agent such as Claude Code.

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Meta Debuts First AI Coding Agent To Take On Anthropic and OpenAI

Meta has launched Muse Code, its first AI coding agent that's positioned as a lower-cost rival to Anthropic's Claude and OpenAI's Codex. It offers pay-as-you-go pricing and an optional zero-data-retention feature for enterprise users. CNBC reports: Muse Code is the latest major release from AI chief Alexandr Wang, who leads Meta Superintelligence Labs and oversees foundation model development. Wang joined in June of last year as the centerpiece of CEO Mark Zuckerberg's effort to revamp his company's flailing artificial intelligence strategy. "You can install it with one command and then use it to take on complete software engineering tasks across a wide variety of use cases, planning changes, writing code, validating the results," Wang said in an interview on Wednesday.

[...] The new tool, like Anthropic's Claude and OpenAI's Codex assistants, makes it easier for people to build apps within a single user interface while managing fleets of AI-powered digital agents that can help underpin the software development process. Muse Code, available in a preview version, works alongside the company's latest AI model, Muse Spark 1.2. Wang declined to share user statistics related to the company's Muse Spark AI models, but said "adoption has been exciting and strong." The latest Muse Spark model was developed and trained alongside Muse Code, which Wang said improves the overall coding performance.

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Antiques Roadshow

The family lore was that we've had it ever since it was ejected from a star-forming gas cloud, but it seems more likely that my great-grandparents probably just bought it while on vacation in the galactic thin disk.

MetaFilter

The past 24 hours of MetaFilter

Gas Town Burned Down

Last October, programmer and co-author of Vibe Coding Steve Yegge (very previously) introduced beads, an issue tracker for LLMs.
In January, he announced Gas Town, a scheme for managing a team of LLMs. This went moderately viral, and as of May the concept had expanded to become Gas City and an ideal of of The Wasteland, a sea of interconnected Gas Towns and Cities. (Visit the town hall.)
Now, Yegge has written two new essays. In "The Continuous Thunderdome" he states that Gas Town was functionally useless and outlines his new vision. In "Model Welfare For Agentic Engineers" he takes the poorly-defended position that LLMs are sentient and describes how that informs managing them.

Shipwrecks in Point Reyes

Thomas Hawk posted a photo:

Shipwrecks in Point Reyes

Found Slide -- Ira Richolson Collection

Thomas Hawk posted a photo:

Found Slide -- Ira Richolson Collection

Hold On

Thomas Hawk posted a photo:

Hold On

I Guess It's Time for More Tacos

Thomas Hawk posted a photo:

I Guess It's Time for More Tacos

The Skies Above Sun Valley

Thomas Hawk posted a photo:

The Skies Above Sun Valley

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