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本页 40 条10月10日 周六
OpenAI revenue keeps surging as company seeks $30 billion in fresh capital
OpenAI's annualized revenue rate sits at about $50 billion, well below the initially reported $70 billion figure that was based on a different accounting method. The correction sent chip stocks sliding. Meanwhile, OpenAI is negotiating at least $30 billion in fresh capital at a $1.4 trillion valuation. The article OpenAI revenue keeps surging as company seeks $30 billion in fresh capital appeared first on The Decoder .
We can’t help treating AI like it’s human. But should we?
"When we are drawn into even the most primitive exchanges with a relational artifact, we believe it cares for us," Dr. Sherry Turkle writes. "And we are wired to care for it in return."
Danu Robotics’ fight to build a better recycling robot
For six years, Danu founder Amy Ma has been working on a better way to sort recyclable waste.
Amazon drops data center NDAs, and AI agents want your credit card
Amazon says it will stop using NDAs when negotiating data center deals with local governments, following a similar move from Microsoft earlier this year. Secrecy has fueled community backlash against AI infrastructure, with opposition leading to hundreds of proposed and enacted moratoriums from New York to San Francisco. Meanwhile, a wave of startups is betting that consumers will hand AI agents access […]
Amazon及其他公司不再对数据中心交易保密。这样足以建立信任吗？
Amazon表示，在与地方政府洽谈数据中心交易时，将不再使用保密协议（NDA）；Microsoft今年早些时候也采取了类似举措。保密行为助长了社区对AI基础设施的反弹，从纽约到旧金山，反对行动已促成数百项拟议及已实施的暂停令。与此同时，一波初创公司正押注于消费者会向AI代理开放访问权限 […]
Show HN: Higherlevel – Define and review what AI agents build
Hi HN! I'm Ryan, I'm building Higherlevel ( https://higherlevel.to ) so product teams have one place to define and review software changes. Over the last couple of years, I've been increasingly delegating software implementation to AI coding agents. However, because it became easier and faster to ship complexity, I realised that it still takes me quite some time to even understand what the software is doing, why it is doing that, or review the changes. I also don't do traditional code reviews anymore, it's mostly automated but I still want to review the final outcome of the changes (rather than its implementation). I regularly work on complex B2B applications where a single feature can involve dozen of business rules, edge cases and interactions with existing functionality. I found myself spending more and more time discovering and explaining requirements to agents, reviewing their output, asking for evdience and trying to establish whether we actually agreed on what correct behaviour looked like. So I built Higherlevel. The idea is to bring product specifications and proof of work into a single collaborative workspace. You can: - describe the current behaviour, known limitations and expected changes - define business rules, acceptance scenarios using Given/When/Then - demand evidence in the form of a screenshot, a video, etc - comment directly on the spec, on a specific area of the image or a timestamp of the video - discuss changes, track revisions and approve results with your team I've written extensively about why I believe in specification driven development (and what it means to me) here https://higherlevel.to/blog/introducing-higherlevel Higherlevel is currently in beta and built with Elixir, Phoenix LiveView, and PostgreSQL. Comments URL: https://news.ycombinator.com/item?id=50023234 Points: 1 # Comments: 0
Ask HN: Internal AI Language
LLMs have an internal language that they translate English into before predicting the next token. Like 'king' is translated into a word of an internal language that corresponds to vector [monarch, man], which allows king-man+woman=queen. Spanish is similar for the case 'queen'=reina, - ina suffix means female, but becomes irregular for king=rey. We have tried to create regular, consistent languages (loglan, lojban, ithkuil), and there seems to be one in the first layers of LLMs, derived from all text ever written. This internal language is currently expressed as vectors, but we could devise a lexicon to map them, and if we could learn it we could communicate more directly with machines, dispensing with some layers and getting rid of language ambiguities. Makes sense? Is someone working on this? It's like Arrival but with AI instead of aliens. Comments URL: https://news.ycombinator.com/item?id=50023533 Points: 1 # Comments: 0
We gave an AI a phone and asked 1000 SF businesses a question
We ran an experiment for SF Tech Week trying to understand how SF businesses are ready for AI. Very soon, every personal assistant like Muse, Instinct, Dots is going to call local places for us, so we wanted to understand what happens. Our AI called the businesses across different categories - vets, bars, cafes, dentists, hair salons etc. It was introducing itself as AI on every call and then asked a question which fits the business like “Are you taking new patients” for dental places. We called only during business hours. What we found: - Only 1 out of 3 businesses kept talking after picking the phone - Vets were 79%, dentists 61%, bars and dry cleaners - around 20% - Most people did not argue, but silently hung up after listening to the intro - 1 out 25 businesses already had AI reception answering the phone Caveats - it is just one city and one week, so small differences between neighbourhoods could be a noise. We would really love to hear how you are handling this if you are building AI voice agents calling places for people Comments URL: https://news.ycombinator.com/item?id=50022739 Points: 1 # Comments: 1
Show HN: This hotel is hella AI-ready. Book directly from AI without MCPs
Hey guys! Excited to show how we were able to get AI agents to read a hotel's live price and availabilities and even create the booking link to hand-off to the user. Get this, all working WITHOUT MCPs or connectors. All on the open web!!! Integrating with this system is possible under each hotel's domain too. Comments URL: https://news.ycombinator.com/item?id=50022896 Points: 1 # Comments: 0
A16z’s Olivia Moore on the state of consumer AI
Moore sees a huge opportunity in consumer AI, particularly if the industry can tap into revenue streams beyond just subscriptions and API charges.
OpenAI revenue falls short, models play hopscotch and Trump cracks down on tech green cards
I’m not going to call the bursting of artificial intelligence bubble yet, not with all that money still pouring into every hardware and software company with AI in their pitch decks. But we got a little taste this week. OpenAI told investors this week that it actually had $18 billion less revenue than the $68 […] The post OpenAI revenue falls short, models play hopscotch and Trump cracks down on tech green cards appeared first on SiliconANGLE .
10月9日 周五
Meatpupptry is far creepier than pure "AI" fakery
Local pharmacy phoneline is answered by "Caroline" with convincing voice, mannerisms and even background typing noise. You only realise she's fake at the first stochastic parrotese. My bank sends emailed query responses signed by e.g. Sarah. No disclaimer, e.g. "AI can make mistakes". Again starts convincing but can degenerate into parrotese. If I politely ask bot/human?, I get "human"... but if I query nonsensical advice, I get a non-resolving answer classic of ChatGPT. The reverse centauar in all its ugly glory. Comments URL: https://news.ycombinator.com/item?id=50021296 Points: 1 # Comments: 0
Quoting Matthew Green
Everyone is very concerned about being respectable, so I’m going to be the goofball who raises worst-case possibilities. I think there is a 1% chance we live in Minicrypt, and a 15% chance we functionally lose confidence in our existing public-key encryption algorithms. [...] The problem here is that the speed of AI producing surprises, and the speed of human beings replacing standards (even with the very best AI assistance) are just orders of magnitude different. You only recover from a surprise like this if you do the preparation in advance. — Matthew Green , on Twitter. I looked it up and Minicrypt is Russell Impagliazzo’s hypothetical world in which public-key encryption is impossible. Tags: ai-security-research , matthew-green , cryptography , standards , llms , ai , generative-ai
18 insights from SailPoint’s Navigate event: Enterprises race to bring identity security for AI agents up to machine speed
AI agents have made identity the front line of enterprise security. Agents now number in the thousands. They pick up access nobody meant to give them, and when they’re blocked partway through a task, they look for another way in. That has turned identity security for AI agents into a board-level priority rather than a […] The post 18 insights from SailPoint’s Navigate event: Enterprises race to bring identity security for AI agents up to machine speed appeared first on SiliconANGLE .