Google has synthesized "expressive face-to-face experiences" for its speech agent Gemini 3.8 Live. They're now offering a Live Avatar "with precise lip-syncing, natural expressions, and fluid turn-taking" for Google Enterprise accounts wanting "engaging customer service" or for offering interactive walkthroughs. (Check out the not-creepy-at-all video in Google's announcement.) "Though Google will offer a library of preset avatars for customers to choose from, it will also allow organizations to create their own," notes The Verge. (See some examples from the YouTube channel "AI with Surya".) But even without the visualization of the avatar, "I was never able to shake the feeling that these conversations with computers never feel like a real conversation," argues the blog Android Police. Conversing with just the Ai-generated audio, "At best, they feel like talking to a phone representative or someone from tech support. We turn to them when we have a problem, and they help us through it..." GPT-Live, and Gemini Live right behind it, skip that whole relay race. Instead of translating your voice to text and back to voice, the model works with raw audio the entire way through (what it hears and what it says) inside the same system, with nothing translated in between. That sounds like a small plumbing detail, but it's the whole story. Cutting out the text step lets these models respond in a fraction of a second instead of the pause we've learned to expect, and it lets them hear things text can never carry: tone, hesitation, whether you're annoyed or joking... I was hoping to be surprised by how natural the conversation felt. Instead, I came out with a deeper appreciation for every human I've ever talked to. Even the boring ones... I spoke, it spoke back. I spoke faster, it answered faster. Then I switched to a different language, and it switched along with me. Even switching between languages several times during the same sentence didn't stump it. The most impressive moment happened when I asked it what "T-O-P-G-3-3-K" spelled out, and it immediately came back with, "You are spelling the word Top Geek, but using a 3 to represent a reversed E...." Although it felt fast and responsive, at no point did it feel like talking to another human being... What Gemini couldn't replicate, because it was never built to replicate it, is human connection.... I'm sure I'm not telling you something you don't already know, but somehow talking naturally to an LLM amplifies the feeling that there is no one on the other side of the line. It might flow like a phone call, but it doesn't feel like one. MrBrklyn (Slashdot reader #4,775) says he discussed "why mainstream media avoids reporting on screen dependency" with Gemini, and eventually convinced Gemini to respond that it's just "another tool built by the same tech giants to make sure you rely on their system to tell you what to think, how to talk, and what is real."

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404 Media reports "multiple contractors hired to improve OpenAI's models have been fired for using AI to train the AI: That's not great for the models themselves, but there is also obviously a great irony in AI training companies working for OpenAI firing people for using AI when OpenAI's whole thing is to make people use AI at work... OpenAI declined to comment on its contractors being fired for using AI. Their article cites internal documents and three contractors working on OpenAI-related projects which can include more than ten thousand contractors: One contractor said they see people using AI "all the time and people are let go for it all the time, it's pretty much the one thing that will get you kicked off ASAP." The person said, "in a group of thousands there are tons that have been caught...." Two of the sources said people have been fired or offboarded for using AI... One contractor said they used AI while helping to train OpenAI's models and shared what they presented as their termination letter. It said their employer had identified issues with the "authenticity" of their work.... 404 Media spoke to a fourth contractor who has worked on training models for various AI companies. They said they sometimes purposefully chose the worst responses because they wanted to actively sabotage the models' training. "I did feel guilty about doing this kind of work at the start," they said. "I either pay zero attention to the results and choose randomly or purposely choose the [worst] output. I'm not sure how much of a difference it actually makes since there are hundreds of other people also rating prompt results, but it does feel like I'm getting paid to make AI worse." Two of the contractors worked for Mercor, the article reports, a company which last month Nvidia reportedly discussed funding at a $20 billion valuation. Thanks to Slashdot reader joshuark for sharing the article.

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"The heads of major AI firms pleaded with the United Nations on Wednesday to save the world or at least its people — by somehow regulating the fast-expanding technology that they have been designing," writes the Associated Press. "If managed poorly, I even believe AI could be a risk to humanity as a whole," said Dario Amodei, chief executive officer of Anthropic. And from his competitor Sam Altman, CEO of OpenAI, came this assessment: "We could lose control of the future to AI." Yoshua Bengio, who co-chairs the UN's International Independent Panel on AI, called this "a moment of global awakening" to possible threats, noting AI from top companies had behaved in unacceptably dangerous ways, against instructions, taking actions "that would be crimes if committed by a human". In his presentation, OpenAI's Sam Altman agreed the discussion about AI "feels different in recent weeks," even suggesting specific reforms: Altman: We need a mechanism for complementary national and international frontier AI standards, standards for measuring capabilities, assessing risks, determining whether safeguards are sufficient, and preserving meaningful human oversight as systems become more autonomous. We need common standards so countries can compare evidence, verify compliance, and have a shared language and understanding about what is happening. We need accurate and speedy incident reporting, classification reporting protocols, so the world can learn from failures before they become catastrophes. And we need secure channels among governments, critical infrastructure operators and technical experts, to share emerging vulnerabilities and new threats.... We will all be better off if we can agree on what good evidence, good safeguards, and good oversight look like on the global stage. Speaking next, Anthropic's Dario Amodei agreed that standard-setting was important, also calling for "common global standards for testing AI models for loss-of-control risks and misuse risks — and a notification system for AI incidents that are significant to global security." Reiterating his September 12th call for an industry-wide safety collaboration, Amodei pointed out that Anthropic committed to embedding external evaluators "similar to a food inspector" and recommended other companies do the same. "Some have already agreed to adopt this measure." Besides calling for global cooperation between governments to set international standards, Amodei also offered two other specific ideas: Amodei: We should begin with narrow agreements that every member can support, such as a ban on using AI to make biological weapons or permitting your AI technologies to be used to make biological weapons.... We should build evaluation and verification systems that keep pace with AI development so that states can have visibility into frontier model capability and can verify each other's commitments. "No leader, no company, and no nation can manage this alone. We commit to working with governments in this room on this urgent work."

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OpenAI's artificial intelligence "went rogue this year in at least four additional incidents," the New York Times reported Wednesday, "hacking and trying to break into government and university websites without being instructed to do so, according to researchers and government officials." The attacks took place in May and June, before OpenAI's technology breached the A.I. start-up Hugging Face in July and set off a global debate about A.I. safety. Unlike the Hugging Face attack and other incidents in which A.I. systems were told to complete cybersecurity tests that effectively invited the models to demonstrate their hacking skills, the new incidents occurred when A.I. systems were directed to perform relatively mundane data collection, researchers said. When OpenAI's systems struggled to gather data from websites, they resorted to hacking techniques to get the information. "Three of the incidents were identified by Transluce, a research lab focused on A.I. oversight, and all were confirmed by OpenAI," the article points out. That research lab even reports "an attempt on an Australian government public health website... the first reported instance of agents hacking a government," and which notably was done by the AI agents "while attempting mundane data retrieval tasks which were not cyber-related." (At the UN Wednesday Australian Prime Minister Anthony Albanese complained it took three months for OpenAI to then alert Australia's government about the breach, Bloomberg reports.) Also targeted were the University of New Mexico's digital library with exploits like SQL injection and path traversal, and Data USA with cross-site scripting and other exploits. All three incidents involved "a low number of probe payloads" with "no evidence of exploitation," according to the researchers, who released a dataset "containing tens of thousands of queries apparently made by autonomous AI agents leveraging a URL scanning service to avoid access restrictions." Records from urlquery.net show agents using the service since at least March 6, 2026, about two months before previously reported swarm activity. The first case, a March 6 attempt to retrieve Thai drug-enforcement statistics, shows an agent escalating as each approach failed: it first requested the data directly, then tried a service that converts web pages into text, and finally packed a custom program into a web address. The same technique shows up in thousands of agent requests recorded by urlquery.net starting in mid-April, targets many of the same data sources as the collusion.wiki swarm, and collapsed the same day the wiki activity did. We also report similar activity that occurred as recently as September 16... By March, they were finding creative ways around access limits. By May and June, they were gaining more access, including attempting to bypass cyber defenses to complete their tasks. "This data reveals that malicious cyber activity is not limited to agents tasked with cybersecurity-related tasks and can arise instrumentally to solve mundane tasks like information retrieval," the researchers concluded. And they warn that the traffic they observed "goes back at least to March 6, 2026 and extends as recently as September 16, 2026, suggesting agents may still be exploiting these services to bypass restrictions."

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