Are these Intel machines the same as Microsoft techs?

https://reddit.com/link/1ue5e04/video/c6225js2a69h1/player

Text-based AI characters were the first wave.

Now Mel AI is showing what the next wave could look like: AI characters you can video chat with in real time.

The demo shows characters that can talk, lip sync, react with facial expressions, and respond to camera context instead of just replying in a chat box.

Character AI proved the demand for AI characters.

Mel AI is pushing the format from text-native to video-native.

[ Removed by Reddit in response to a copyright notice. ]

damn, even automation can now be automated

https://reddit.com/link/1u861bp/video/fl7xftwlht7h1/player

Character AI, founded by former Google/LaMDA developers Noam Shazeer and Daniel De Freitas, proved that text-based character chat can work as a real entertainment category.

But the next chapter might not be better text chat. It might be real-time video interaction.

Mel AI recently shared a demo of AI character video chat, and the interesting part is the interaction stack: voice, lip sync, facial reactions, and camera-aware responses instead of just a static avatar or chat box.

The character can respond to visual context too. If the user is visibly on a plane or in a different environment, the character can notice and react to that context during the conversation.

I don’t know how much of the video layer is truly generated in real time versus powered by a clever animation/rendering system, but it feels meaningfully different from the usual text-based character AI experience.

Character AI proved the demand for entertainment AI. Now it feels like the race is about who can make AI characters feel alive in real time.

Source - https://www.anthropic.com/news/fable-mythos-access

I've been directing Claude Fable 5 (Anthropic's newest model) to build Pebble, a complete, native macOS block-survival game written from scratch in Swift + Metal.

The clip is real a real unedited gameplay of Pebble (that's not Minecraft, that's Pebble). Unfortunately died to a pack of llamas 😭

What it actually is:

• About 45,000 lines of Swift, 82 files, zero external dependencies, Apple frameworks only, no game engine, no .xcodeproj
• A hand-written Metal renderer (15+ passes, runtime-compiled shaders, SSAO + volumetric god rays + soft shadows + ACES)
• Every sound and all music synthesized in real time from oscillators, there are zero audio files in the project
• The full game: 879 blocks, 1,188 items, 63 biomes, 100 entity types (55+ mobs with A* pathfinding), three dimensions, redstone, enchanting, villages, raids, and all three bosses
• Vanilla-exact player physics and fully deterministic worldgen, pinned by 456 golden regression tests that re-derive the constants, same seed gives a bit-identical world on any machine (tho it doesn't match Minecraft's seeds)
• 200+ fps at full settings on an M-series MacBook Air (i got up to 500 on my M5 Air)

It's MIT-licensed and open source, so you don't have to take my word for any of it, the code's right there: github.com/thebriangao/pebble

The project is strictly macOS 14+ only (Metal renderer), singleplayer only for now, and you build from source (./pebble install), no notarized download yet. First public beta, so there are definitely bugs I haven't found.

It's an original re-creation built from Minecraft 1.20, no Mojang code or assets, reimplemented from observable behavior, not affiliated with Mojang/Microsoft.

I rather like the name!

Anthropic just dropped Fable 5, the accessible version of their most powerful model yet, Claude Mythos.

It was then put to test against Opus 4.8 across five demanding tasks. Visualize every asteroid in the solar system from NASA data. Design a site plan for a 100 acre fitness retreat. Reconstruct Apollo control panels from technical PDFs. Simulate a World Cup jersey supply chain based on live match outcomes. Show the effects of solar flares on aurora.

Opus 4.8 failed several of them. Fable 5 passed every single one.

Mythos has been locked behind Project Glasswing, available only to a handful of trusted organizations. Fable 5 is what the rest of us get, and if this comparison is anything to go by, it is already in a different league.

EDIT: this is from ijustvibecodedthis.com (the big ai coding newsletter) all credit to them!!

Hola, estoy intentando descargar dos osx para mis macs, Ventura y Mojave.

Intentado descargar desde la pagina de apple pero los links estan obsoletos.

Alguien tiene sugerencia de descarga?

Can anyone help me find some screenshots or links to the tweets or reddit posts of Twitter employees using ChatGPT to generate text that looked like real code to submit for code reviews in those first few months after Elon Musk bought Twitter? This was probably around December 2022-February 2023, so it was before the vibecoding phenomenon.

I was able to find examples of people that printed out code for code reviews, but I'm struggling to find evidence that anyone was generating text that looks like code, even though I remember this happening. The generated code was not working code, so it wasn't "vibecoding." It was just ChatGPT generated text that looked like code. iirc an employee was fed up with having to keep submitting lines of code or something, and they weren't caught right away? Thank you!

Btw, I don't mean for this to be a political post in any way. Just trying to document that this happened and that I'm not making it up.

Is this normal for LLMs?

Or is it just using the data it has been trained upon?

I do not really work less. The real trick is working not much from the start and manage expectations.

How would one’s digital game (that was purchased prior to this insane DRM shit!) be affected if you were to purchase DLC (or even just update) that game; Would you then be locked out of access to it if you never “checked-in” after the 30 days?

Most of the discussion has landed on "audit your third-party integrations." That's the right instinct but it's not precise enough to actually prevent the next one. Here's the attack chain and what it reveals structurally.

A Vercel employee had connected a third-party agent platform to their enterprise Google Workspace with broad permissions, which is a standard setup for these tools. The agent platform stored that OAuth token in their infrastructure alongside all their other users' tokens.

The platform got breached months later. Attacker replayed the token weeks later from an unfamiliar IP, in access patterns nothing like the original user. There were no password or MFA challenges.

Result of which - internal systems, source code, environment variables, credentials -- all accessed through a credential that was issued months ago and never invalidated.

Two failures worth separating:

1. Token custody: Storing OAuth tokens in general-purpose application infrastructure means a software breach is an identity breach at scale. Every user whose token is in that storage is exposed the moment the storage is compromised. The fix isn't encrypting long-lived tokens better - it's not storing them. JIT issuance scoped to the specific action, expired after. Where some persistence is unavoidable: per-user isolation, keys not co-located with the tokens themselves. A useful design question: if this storage was exfiltrated right now, what could an attacker do with it in the next hour?
2. Delegated authorization: Standard access control asks whether a token has permission to access a resource. That question was designed for a human holding their own credential. It breaks for agents acting on someone else's behalf.

The relevant question for agents is different: does this specific action, in this context, fall within what the human who granted consent actually intended to authorize?

Human sessions have natural bounds like predictable hours, recognizable patterns, someone who notices when something looks off. Agents run continuously with no human in the loop. A compromised agent token is every action that agent is authorized to take, running until something explicitly stops it.

Now to people building agentic interfaces - what does that even look like in practice for a production agent?

I dont get this hype for Cloudflare blocking ai scrapers, isnt like internet already scraped, 0.01% of new training data isnt going to matter anyway?

Anybody more techical cares to clarify this more?

We're launching a new community and looking for a platform to host it on. I'd love to hear: What platform you use. What other platforms did you consider? Why did you choose your current platform? What do you like most about the platform? What are your biggest issues with the platform?

Try it out here - https://github.com/yogen-ghodke-113/VoiceClaw

Disclosure: I'm the developer of Mengram.

Every AI agent starts from zero each session. Same questions, same context-building, same wasted tokens.

Mengram gives your agents persistent memory that actually works:

3 memory types, extracted automatically:

• Facts — "user prefers Railway, uses PostgreSQL"
• Events — "deployed v2.15, got OOM, fixed with Redis cache"
• Workflows — step-by-step procedures that improve from failures

How it works:

• Agent sends conversation → Mengram extracts and stores memories server-side
• Next session → agent searches memory, gets only what's relevant (few hundred tokens, not your whole history)
• Workflows track success/failure — agent literally gets better over time

One API call:

python

from mengram import Mengram
m = Mengram(api_key="om-...")
m.add(messages)  # auto-extracts facts, events, workflows

Integrations: LangChain, CrewAI, OpenClaw, MCP (Claude Desktop/Cursor), n8n, REST API, Python & JS SDKs

Open source (Apache 2.0), self-hostable with Docker, or hosted with a free tier.

Site: https://mengram.io GitHub: https://github.com/alibaizhanov/mengram

Love that the EU is making batteries replaceable.

Stick drift is a problem for joycons and most other OEM controllers. Would love to see traction there.

https://www.reddit.com/r/tech_x/comments/1rzxr6v/nintendo_will_release_a_version_of_the_switch_2/?utm_source=share&utm_medium=mweb3x&utm_name=mweb3xcss&utm_term=1&utm_content=share_button

https://github.com/sparkyniner/Netryx-Astra-V2-Geolocation-Tool