i keep watching people walk right past the door and the door to local ai is a 12, 16 or 24gb gaming gpu > the rtx 3060 is still the #1# desktop gpu on steam > 16gb is now the most common vram on steam, 26.9% of everyone > 65.7% of steam sits between 8 and 16gb that's the hardware. here's what it runs today, measured: > 8gb: 27b with a 48k ctx > 12gb: that same 27b at 50.8 tok/s with 131k ctx > 16gb: 262k ctx, and it sees > 24gb: the king qwen 3.8 27b q4 a lot of the people arguing would never spend $500 on the card that ends the argument. yes, gpu prices are dumb right now. it's still the cheapest seat you'll ever buy in this race because the second the model runs on your own card, the rules flip i watched opus 5.5 get cut off for reading anthropic's own blog. my local model has never cut me off once. it runs with the wifi off, it does the tasks the cloud won't touch, and for the first time you get to taste what owning your thinking actually feels like local ai is the most underrated, under adopted thing, and the door is already sitting in two thirds of the gaming pcs on steam what card is in your rig right now?

i keep sharing my trades and thoughts on ct because i know how much it helped me when i was starting out back in 2017, there were traders who had already made it but still chose to share their knowledge and help others learn i benefited a lot from those people, and i want to do the same for the next generation of traders the criticism comes with being public, but i've never felt that was a good enough reason to stop sharing what i've learned

I keep wanting to add new features to my bookwriter and scriptwriter. I start planning that feature. And then I realize that I don't need it because I can just instruct an agent to change the files. A lot of the features we used to add to projects was to eliminate the hassle of manipulating the underlying files ourselves. Now we can have agents do that rather than implementing feature on top of feature on top of feature.

I keep saying it, this is a trader's market. Holding high growth names straight through has been brutal. You have to adapt. Add weakness, trim strength, repeat. Been playing these well. Here's one from Friday nearly catching the top of both companies.

I keep coming back to this @ArtificialAnlys chart of the dotted Pareto line shows the models offering the most benchmark performance at each cost level, but the cheapest model on that line isn’t automatically the right one for every task. For high volume, repeatable work, I’d start with something like @OpenAI GPT-6 Luna and see if it clears the accuracy bar. GPT-6.1 Sol looks like a compelling middle ground, but for the harder steps where a better answer changes the outcome paying up for @claudeai Opus 5.5 can make sense. On this chart Opus costs roughly 8x as much per task as 6.1 Sol. You want to keep thinking about which steps actually earn that extra spend because as agents make more calls getting that routing decision right could matter a lot. ---> continuing in a second post

I keep seeing every new tokenized asset launch described as RWA adoption. I don’t think issuance alone tells us that. So I went back to @coingecko’s RWA Charts and compared the live market cap with actual trading activity. Right now, tokenized RWA market cap is $9.04B, up 6.3% in 24H. Meanwhile, trading volume has reached $1.64B, up 148.2%. That volume is equivalent to roughly 18% of the entire market cap in one day. This was the part that caught my attention. The asset base is growing, but activity is accelerating much faster than the value being tokenized. It doesn’t automatically mean the whole RWA market is becoming liquid. One asset or issuer could be driving most of the spike. But where is the volume actually coming from? This is how I use the page: → Compare market cap by asset type → Check whether volume follows the same category → Switch to issuer view to see who controls the activity → Use token count to separate real demand from simply adding more listings → Move between 24H, 3M, 1Y and Max to check whether the move is temporary or structural For example, if token count rises but volume per asset stays weak, the sector is expanding in supply, not necessarily adoption. If market cap, volume and issuer activity grow together across longer timeframes, that is a much stronger signal. This is why I find the page useful. It lets me separate 2 things people often treat as the same: → More assets tokenized → More capital represented onchain → More users actually trading them The current volume spike is worth investigating, but the asset-type and issuer breakdown will tell us whether it is broad RWA growth or concentrated activity. Explore the live data and run your own comparison here: