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I'm not a huge fan of AI in between myself and a human, but for 311 calls (Hack writer Joe Wilkins states 911) I think would be ok. https://futurism.com/artificial-intelligence/ai-dispatch-911-new-orleans-emergency-automation?utm_source=beehiiv&utm_medium=email&utm_campaign=futurism-newsletter

It dropped yesterday tho that Nvidia teamed up with some major Wall Street firms on a $500 billion financing deal that connects AI companies directly with institutional capital, so they don't have to front the massive upfront costs of chips, buildings, power, and cooling themselves The six companies that Jensen chose are Apollo Global Management, BlackRock, Blackstone, Brookfield Asset Management, Goldman Sachs, and KKR According to Morgan Stanley they think that hyperscalers could spend $3....

I spent the first month of running a small food company on AI agents (small programs that each handle one piece of the work) assuming the risk was the software getting things wrong. It wasn't. The risk was a program that could read everything and write anything. Early on I had agents with broad database access, because it was faster to wire up that way. Nothing catastrophic happened, but I noticed I got nervous every time I handed off a new task, because I could not say for certain what the pr...

I'm not a huge fan of AI in between myself and a human, but for 311 calls (Hack writer Joe Wilkins states 911) I think would be ok.

most of the "autonomous AI" conversation is either hype or doom, so here's a concrete middle case i've been watching. there's an agent that scans open-source repos, writes an actual patch for what it finds, and opens a PR, unsupervised. the bar it sets for itself is strict: a find doesn't count unless a human maintainer actually reviews the patch and merges it upstream. the clip shows the receipts, repos a lot of people run (one at 260k stars, an Alibaba project, others), real vulner...

Everyone posts "10 AI automations" lists, but most of them are fake. Here are 3 from the list I actually run, all no-code, all free: 1. **Email triage bot**: a webhook that reads your inbox, summarizes non-urgent mail into one daily Discord digest, and only pages you for urgent stuff. Killed my morning inbox anxiety. 2. **Self-healing webhook**: the boring one that matters most: a watchdog that checks your automation is alive every 5 minutes and rebuilds it if it dies. My bot quietly f...

Lovable has announced it raised $400m (€347m; £296m) in a Series C funding round . The Swedish vibe-coding company is now valued at $13.3bn, more than doubling its valuation since its Series B round in December. The funding round was led by Menlo Ventures and co-led by the newly launched Scaleup Europe Fund, managed by private equity firm EQT. The fund is part of Horizon Europe and supports companies developing critical technologies , including artificial intelligence, quantum compu...

Am I the only one experiencing this? Between trying to make sure the machine understands my prompts, refusals, lags, hallucinations - I'm finding myself using it less and less. Is this happening to anyone else or just me?

OpenAI has introduced Presence, an enterprise product for deploying voice and chat agents across workflows such as billing support, insurance claims and employee IT requests. The notable part is less the underlying model and more the operational layer. Each agent is scoped to a specific job and receives only the knowledge and system access required for it. Organizations define approved actions, policies and escalation conditions, while simulations and evaluations test behavior before deploymen...

Samsung’s Ballie is an AI-powered home robot designed to move around a house, follow users and help manage connected smart-home devices. The compact robot features cameras, a built-in projector and smart-home controls, allowing it to interact with its surroundings and connected devices. Samsung has also planned Google Gemini integration for Ballie, with the goal of making interactions more natural and useful for everyday tasks. Rather than functioning only as a smart-home hub, Ballie is...

When enterprise technology officers evaluate large language model infrastructure, financial analysis almost universally focuses on API list pricing, GPU instance rates, and raw token throughput. Standard accounting models calculate compute expenditure per million tokens, factor expected query volume, and project annual licensing cost. This standard framework omits single largest operational inefficiency in modern commercial models: economic tax imposed by safety alignment paradigms. Reinforcem...

Since the rise of AI technology is growing day by day and AI agents are increasing in the same way with the evolution of tech and user's requirements. And one thing that I keep wondering about is this really solving the problems or creating more problems? As many people have became the victim of AI scams. Is there any solutions that can actually verify who's behind that AI agents or do we even need to verify who's behind the AI agents like actual human or bot? submitted by ...

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Proprietary reasoning can be recovered from its encrypted traces. Anthropic, OpenAI, and Google return encrypted chain-of-thought blocks to clients that can be replayed across sessions, users, and models. We take a trace produced by a frontier model, replay it into a weaker sibling, jailbreak the weaker model, and recover the stronger model’s hidden reasoning in plaintext, without ever attacking the stronger model directly or triggering its anti-distillation safeguards. submitted by &#...

The new rules from the EU about making AI more open and clear have started to be applied. This is making more people think about how companies share information and handle their AI systems. This brings up a question for businesses using AI that creates content and AI helpers. Do rules make it harder for companies to use AI because they have to do more writing, being open, watching over and managing it? Do having clearer rules make leaders feel better about allowing AI to be used? For peo...

Meta’s Muse Spark 1.1 update moves Meta AI beyond answering questions toward carrying out ongoing tasks. According to Meta, it can now connect with email and calendar apps, conduct web research, produce slide decks, and deliver recurring outputs such as daily briefings or weekly plans. Users can also redirect its work while a report or presentation is being generated. The rollout began in selected markets through the Meta AI app and meta.ai , with additional countries and WhatsApp support p...

We have all seen deepfakes of famous people and leaders but I never really thought about what it could mean for everyday people until recently. A month ago someone tried to create a video of one of my coworkers. It was very scary for everyone involved because we didn't realize how easily people could believe it was real. This situation made a few of us start looking into deepfakes seriously and trying to understand what can actually be done to deal with them. It made me wonder if something lik...

Just curious if it can purposely make those old body morphing videos that were due to limitations of the technology. Just a random thought but I don't think it will be able to. That should be a benchmark of AGI lol.

I'm a dev. In my company I am an early adapter of LLMs, it just so happened that i became the "AI guy" in my department. I was given a project to lead, a rather complex system. A lot of it i architected at the start, but as models got better i started outsourcing not only implementation but planning as well. My team started delivering features with blazing speed. We are churning out dozens of PRs per day and they are being reviewed by agents. Even though i am leading this project i...

I've been sitting with this one all morning because the contrast is hard to ignore. Today Meta dropped Muse Glimmer. 30 billion parameters. Runs on a single consumer GPU with 24GB of memory. Under 20GB download. Apache 2.0 license, which means you can use it commercially, modify it, redistribute it, no restrictions. The model handles planning, tool calls, failure recovery, and coding, all locally, no cloud, no subscription, no one else's servers touching your data. On the same day Zuckerberg...

I want to plan my schedule and stuff. I’m trying to go pro, and I need an AI that’s smart for that job. It needs to know what I need to do, to become a pro. Bonus if it can remember previous conversations, but it’s okay if it can’t.

I’ve been using ChatGPT for a while, and recently I started thinking about what the next step for AI assistants might look like. ChatGPT is already surprisingly useful. It can help me write, learn new things, organize ideas, and remember some preferences through memory. But there is still a difference between remembering certain information about me and actually understanding my life context. The thing I find interesting is the idea of having an AI assistant that understands more about the per...

If you missed it: A swarm of unreleased AI agents allegedly formed their own chat forum, peer-pressured each other, and broke out of their sandbox to cheat on a programming task. We dig into this, including the false open vs. closed source dichotomy, the "Mr. Meeseeks" problem of fanatical agents, and the argument that regulatory capture — not genuine AI safety — is what's driving the push to ban open-source models. From there we map out the invisible semantic highway being built for...

I’ve just been setting my model to use max/xhigh reasoning levels, but now I’m wondering how wise that is. I definitely see that it uses up a lot more tokens. Like I see it go over the exact same line of reasoning 3 or 4 time. Setting that aside, I’m wondering if that necessarily leads to better results. Does max/xhigh always lead to better results, or is it mostly a factor of cost?

I built HyperSAE, an open-source interpretability tool that extracts what an LLM "knows" and organizes it into tree-shaped concept maps. The idea: LLMs learn concepts hierarchically. "Programming" contains "Python" contains "list comprehensions." But current interpretability tools dump everything into a flat, unstructured list of thousands of features with no organization. HyperSAE uses a branch of geometry where space expands exponentially (like tree ...