Darshan Ponikar 🧑🏼‍💻

this is whats going to happen to epic games in about a year

Craziest use-case of Muse that I heard at a dinner event: CTO wanted to get SOC2 done. Gets muse to reach out to 6 vendors that target startups of his scale. All of them interested. His Muse reviewed each of them, their quality / outcomes, negotiated and got him a deal that beat the market.

We asked GPT-6 Astra to edit Qwen3.5-0.8B weights to improve math. It directly changed only 0.016% of weights, fixing 0.8B's reasoning loops & improving math up to 6x and even instruction following 3x, without gradients or training. We call this Weight-Space Programming: frontier LLMs can now natively read/write neural network weights! 🧵 Blog: rikiyat.github.io/blog/weigh…

Seeing this makes the end-state clearer to me: code that can't be read by humans, run on machines that humans can't access, via inaccessible APIs, trained on data that humans didn't create. LLMs are starting to get really good at manipulating mostly-opaque-to-humans code (see: their improved ability to reverse engineer machine code/assembly). Additionally, folks are accessing more-and-more of their LLMs in cloud-based environments without ever actually interacting with an LLM API (myself included). I think it's going to become increasingly likely that the end state is one in which you ask an agentic company to produce some result and it does it via [some system completely opaque to humans] and produces [some output in a format that humans are unable to interpret]. It makes me wonder if our current state of competing LLMs cross-training on each other will eventually become literally impossible (not just logistically so) when they become fully self-recursive and are producing output that even other LLMs can't understand, let alone humans. I think we're in something of a golden period here where humans are still capable of understanding how things work and how things are run (shell commands! python! node.js!) but it's going to quickly become irrelevant. We're already past the previous high-point where we were able to see reasoning traces for the top-level LLMs. I'm skeptical that open models will ever get to this point as the economics are working against them (I suspect that they will always need human-generated training materials in one form or another). But it does make me wonder if the upper-echelon companies will end up converging into this high-level "black box that produces outputs" singularity of sorts. This has been hitting home for me lately as I've been using Claude Projects in a cloud-based environment where I can't see transcripts, look at the machine it's running on, nor even know what commands it's running. I don't even know what languages its writing its code in. We're just a couple steps away from code being completely irrelevant.

i read this at least once a month.

An urgent notice from the Railway team blog.railway.com/p/security-…

I may end up missing Navratri this year, but last year’s Navratri wasn’t good either. I was surrounded by thousands of people, yet I still felt alone.

After years of declining subscriber numbers and falling revenue, Bumble just agreed to a $1.3 billion acquisition. spr.ly/6016BHEq0m

BREAKING: 🇺🇸 US suspends the following companies from the green card program: 🇺🇸 Microsoft 🇺🇸 Adobe 🇮🇳 TCS 🇮🇳 Infosys 🇮🇳 Wipro 🇮🇳 HCL 🇺🇸 Cognizant 🇫🇷 Capgemini

August was my last month at @huddle01com. For nearly six years I was the only product designer there, working on everything from fundraising pitch decks to mobile apps, dashboards, websites and the brand. What a blessing it was. Thank you to @ranjan3118, @Susmit_Lavania, and a team that was generous, smart and fun to build with. Now contracting with two companies, with room for one more contract project. If you're building something, I'd love to hear about it. p.s. My design work has its own home now. Small tools, design resources, and the odd, chaotic stuff, all at @pixelyokai.

Ben Affleck reveals he writes Python, understands convolutional neural networks, worked extensively with GPUs, and used his celebrity status to get private looks at Google and OpenAI’s video models “I’ve always been kind of into computers since I was young. Then, when film started to move from analog film to digital, I became more interested in that aspect of it. The visual-effects workflow for many years has included machine learning, so I can write pretty shitty Python scripts and stuff like that. “With convolutional neural networks, which were the precursors to what the transformer can do, which is much more computation simultaneously, you would do things like look at what’s called a tensor. That’s the numerical translation of a visual image in numbers, like the batch number, the frame number and the red, green and blue values of each pixel in each frame. It’s just that simple. That numeric is called a tensor. “You’d use a convolutional neural network to identify patterns that reveal what’s called edge detection or feature extraction, which is identifying patterns well enough to know, this is where the window ledge is, so we can more easily take the green-screen image out and replace it with something. “That was familiar to me early on because, prior to Artists Equity, I had a small visual-effects company. I’ve worked with GPUs a lot too. The visual-effects guys said, ‘Hey, you should see. There are a couple: Google and this other company, OpenAI, are doing really interesting stuff with transformers in video.’ “I’ve learned that I can actually just call up and go, ‘Hey, it’s Ben Affleck. Can I come see what you’re doing?’ Sometimes people say yes, to my astonishment.”

GTA 5 on Snapdragon 8 Elite Extreme Gen 6 - Xiaomi 18 Pro Max MIND BLOWING PERFORMANCE!