submitted by /u/whenyoupeeupsidedown [link] [留言]

Back in '24, there was a story about GPT-2 being run on excel https://arstechnica.com/information-technology/2024/03/once-too-scary-to-release-gpt-2-gets-squeezed-into-an-excel-spreadsheet/ How hard/$/time would it be to recreate GPT-4 (or equivalent)? GPT-4 was released in '23, since then there have been more/better chips, etc. Is this something a competent S&P500 company could do on its own? submitted by /u/tjdogger [link] [留言]

Now I myself have not used AI a ton beyond making a funny picture or two on ChatGPT/Gemini and maybe asking it a few things on the fly if I need a second opinion on something - and sometimes it's been helpful. The biggest thing I hear from the "Fuck AI" crowd is that it ruins the creative circles like artists, authors, etc. because it copies their work. I sympathize with their hate, but I've heard an argument that it's not doing anything different than what we do when/if AI didn't play a role in anything: look at other people's work for inspiration then create something. Like we can't create a song in a vacuum, we need to learn and be exposed to music theory, notes, other styles of music, instruments, etc. So someone starting a band didn't make something brand new, it took pieces from other artists. And the part that makes me sing AIs praises, so to speak, is its use in the medical field. Doctor Mike posted a video about a year ago talking about this. Like, if it's improving healthcare to the point that it's detecting life threatening things to help doctors treat and cure us more effectively and efficiently, why are we trying to get rid of it? Maybe that's not what people are saying when they want AI gone or saying how 'awful' it is, but I just hope we don't end up throwing the baby out with the bathwater with AI because I genuinely think it's an astonishing thing that's clearly helpful in certain circles. submitted by /u/SeaGlass_7 [link] [留言]

NASA is targeting an August 30 launch for the Nancy Grace Roman Space Telescope, which has 100 times Hubble's field of view.

Facebook has long been filled with feeds of clickbait articles. Now, Meta is making its own clickbait articles with AI. The standalone Meta AI app now has a "For You" section that populates a list of clickbait-style stories for you to read. But the topics, images, and text are all AI-generated - and as questionable […]

Check out all the Summer Game Fest showcases you can watch today, June 6.

Hi all, About three years ago I built a small library called Trig.js to expose scroll data to CSS via data‑attributes. It recently got highlighted as one of the “Enterprise Heavyweights” of scroll animation libraries by CSSAuthor, which made me revisit the idea. I’d always planned to make a Cursor.js, so I built it and then I started wondering, what else could be exposed to CSS variables? That question spiralled into something bigger, and I’ve now ended up creating a full stack of small, browser‑native libraries that all share the same philosophy: Once I reached Keys.js, something clicked. Keys aren’t animation, they’re input. That led to the bigger question, could you build full applications or even games this way? The answer turned out to be yes, and that’s when I came up with State.js. For the first time, here’s the full stack together: Trig-js - exposes scroll data to CSS Cursor.js - exposes mouse/touch position Motion.js - a global clock for CSS‑driven animation Keys.js - exposes keyboard input State.js - a reactive state layer for HTML Gravity.js - a DOM‑element physics engine rendered in CSS Together, these for a declarative application/game engine using the native browser without webGL, webGPU or canvas. Your HTML is your state graph, the CSS is your rendering engine and JS becomes the wiring that connects everything up. These libraries all work independently or together. As every one of these open up capabilities that wasn't possible before that's why they are all individual so you can pick or choose or use them altogether for a complete stack. A few months ago I wouldn’t have believed half of this was possible in the browser without heavy abstractions. It’s made me realise how much capability we’ve historically hidden behind frameworks instead of exposing directly. I’m excited to share this approach and would love to hear your thoughts, ideas, or critiques. If you’re curious about browser‑native reactivity or CSS‑driven rendering, I’m happy to dive deeper.

Whether you hate subscriptions like Kindle Unlimited or simply want to get away from Amazon for whatever reason, you'll find plenty of solid options available.

For over a decade, the standard approach to bot mitigation has relied on a fundamentally flawed premise: tracking every micro-movement a user makes. The industry standard "invisible" CAPTCHAs ingest your mouse curves, touch pressure, scrolling behavior, and browser history to calculate a "human score." At Conversion.business , we took the opposite approach. We built a zero-telemetry, privacy-first Gamified CAPTCHA platform that tracks no behavioral interactions. Instead, we rely on a mathematically rigorous Game Randomization Strategy and a strict cryptographic handshake. Here is the architectural teardown of why standard machine learning fails against our engine, and why discarding behavioral telemetry actually increases security. The Flaw in "Invisible" Telemetry Standard CAPTCHA systems rely on security through obscurity. They collect massive amounts of user telemetry and run it through proprietary risk-analysis models. This creates two massive problems: The Privacy Tax: You are forcing your users to surrender behavioral biometric data just to log in. The ML Training Loop: If an attacker can reverse-engineer the "human" mouse-curve threshold, they can train a bot to inject fake cursor paths. Once the model is trained, the security layer is completely compromised until the vendor updates their algorithm. The Conversion.business Approach: Zero Telemetry Our OopsSDK does not track mouse movements, touch pressure, or cross-site cookies. We rely on a lean, transparent Verification Signature that collects only: solveTimeMs : The exact duration from puzzle initialization to completion. webglFingerprint : Hashed hardware renderer info. userAgent : To identify known headless browsers. How do we stop bots without tracking behavior? By attacking the core requirement of machine learning: predictability . The Game Randomization Strategy Machine learning models, specifically reinforcement learning and computer vision bots, require a predictable environment to train effectively

Okay so I've been thinking about this a lot lately and I feel like everyone's still stuck on the "which model is best" debate when there's a completely different cost problem creeping up on companies actually deploying this stuff. It's not the model. it's the steps. Like... a browser agent doing something that sounds simple: fill out a form, grab data from a dashboard, submit a thing. that's not 3 steps. that's observe, click, wait, observe again, oh there's a modal now, handle that, screenshot is stale, retry, login broke, start over. easily 30-50 tool calls for a task a human would do in 90 seconds. At a small scale you don't care. annoying but whatever. at company scale? If you're running agents across customer ops, internal tooling, research, travel booking, job pipelines, etc., that inefficiency compounds really fast. I came across something called ego lite which apparently takes a different approach: isolated sessions per task, reusable login state, better page snapshots, JS-level orchestration so agents can chain actions instead of calling tiny tools one by one. they're claiming 20-50% faster completion on comparable tasks which honestly if true is not a small number when you're paying per token per call. idk maybe I'm in the weeds on this and most companies aren't at the scale where it bites yet. but it feels like one of those things where by the time people notice the bill, the architecture decisions are already locked in. the smartest model running in a bad environment is still a slow expensive agent. Anyone else actually tracking execution efficiency as a real cost metric or is it still mostly vibes and benchmarks out there? submitted by /u/babyb01 [link] [留言]

Pretty basic question, I’m curious to know what the most useful thing you’re using AI for? Are you using things like Claude cowork for tasks, Codex or Claude code for programming, script writing, homework? Do you use it as a regular chat for companionship, are you using it for life advice? Really just curious how individuals are finding it useful to them Thanks submitted by /u/thomas_unise [link] [留言]

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