YIKES 😬 Nvidia will apparently END production for the RTX 5090 to allocate the GB202 chips to the AI workstation cards (RTX 5000, 5500, 6000 Pros) Will gamers get a replacement flagship or is the 5080 it now?

Here’s essentially the expansion board broken down. It’s got two PCIE switches inside, meaning that you only need a singular x16 slot to power 8 GPUs (or two). Let’s talk about how it works. First, the main 8 GPUs slots You have two methods of setup here: - Direct connect via two PCIE x16 -> 4x x8 MCIO - Cascade via a single PCIE x16 -> 2x x8 MCIO The difference here is how much of your GPU usage do you want heading back to your CPU vs keeping everyone around one dimension for faster GPU -> GPU communication. A quick way to think about it: model fits on 8 GPUs? Cascade. CPU offload? Probably direct connect. But what IS cascade? Let’s look back at the diagram. Direct connect says that we’re going to plug in two slots worth of x8 connectors into both 0-7 and 8-15 slots (two halves of our PCIE x16) into the separate halves. This then populates the switch in such a way that we can support 8 GPUs, each on separate 4-GPU P2P groupings. The nice part here is because the PCIE switches live in this board, you can take four additional MCIO cables and go from the output downlink into any one of the direct connect interfaces and add an additional GPU. BUT, if you want the two groups of 4 GPUs to interact, they’ll get tunneled through a single x16 slot worth of transfer, and have to go through the CPU. Not a fun bottleneck when dealing with 64 lanes worth of GPUs on either side. The alternative is what we call “cascade.” If we don’t want to worry about the CPU side (e.g. model inference), we can instead only hook up one PCIE slot as the input, then take the downlink from SW1 and use it as the INPUT to SW2. It’s still the bandwidth of a singular PCIE5 x16 slot, but you avoid going through the CPU which saves you some cycles. For the full 12 GPUs, you would need 3-4 full x16 slots on your motherboard. With the direct connect slots running through the host CPU still (since they are direct connect), if you’re not doing cascading. Or translation: - Non-DC: slot 1 and slot 12 are powered through additional retimers and MCIO at x16 and don’t add a slot, it’s just moving your existing PCIE slots somewhere else. Then you power slots 2 and 11 through the “jump” mentioned earlier - DC: slot 1, 12, and then 2 or 11 are powered through a retimer, and then the other (between 2 and 11) are powered through the “jump” Now let’s get into how I plan to use this. I have 9 GPUs in total (8 6000’s and a 6000 ADA), so I’ll be doing the Cascade, then using the SW2 output to power a 9th PCIE slot similar to the non-Cascade version that could power 10. What I don’t know yet is which is better: TP4/PP2, or TP8 over the two P2P groups, but I expect that would be the difference of batching. I’ll probably accept some slowness and do TP8. I can’t predict how much slower that will be, so when it comes in I’ll do these full benchmarks in many different combinations. What I want you to gather from this is these boards have internal PCIE switches, to help avoid needing to go through the CPU to have your GPUs interact, and bring you a larger lane budget than your CPU would allow.

I was at an AI dinner last night in NYC. Some interesting topics discussed 1. Performance engineers now spend most of their time managing agents and RSI loops. Most perf opts at major inference providers (together, fireworks) are found by agents. 2. RLing too much on code and math has negative effects on your model especially it’s language. 3. People were impressed by @bot and the overall acquisition of @cursor_ai by @spacexai. xAI is a legitimate frontier lab right now. 4. Most people have agents in loop writing, reviewing, and submitting PRs 24/7 5. Most agreed code review is not super productive anymore 6. Consensus was Fable 5.5 will be stunning but OpenAI will beat it in December with Bel

We're hiring exceptional engineers to join the team. No degree required. All we care about is you being smart and able to solve hard problems. Total comp is $550k-$1.1M (job ad says something else, but ignore that).

@GIGABYTEUSA Rejected this 4090 customer card for RMA. The gpu core and memory were perfectly still working, so I just put them on a new gigabyte 4090 pcb, and now the customer has a working gpu. Why doesn't gigabyte offer this service?

y'all realize max reasoning is a waste of money right? astra on max costs way more than xhigh and literally scores worse on terminal bench 4 for most of my coding tasks, high gives me basically the same results for way less i'd love for someone to prove me wrong though

Excited to announce that all super intelligence organizations have now jointly agreed to the ultimate in AI/SI safety: Moving all testing to Delta Airlines flights, where accessing the Internet is utterly impossible!

I find myself reaching for Davinci, CapCut, Premier - or any video editor, FAR less. Everything you see in this video was done entirely in Claude desktop: Color grading, audio mixing, motion graphics, transitions, speed adjustment, matching voiceover and camera to the timeline, building the teleprompter, zoom effects, everything. No video editor. Only natural language. I'm not sure there will ever come a time when that doesn't blow my mind.

I think it's pretty clear that Cursor saved xAI. Just a few months ago, they were the butt of almost every joke (the ones not made about Mistral anyway) Who's laughing now? No one. Take this as a lesson next time that you hear someone say that some company "is cooked." All of these labs are just one killer product, or one killer model, away from being talked about everywhere. Count out Google, xAI, Meta etc at your own peril. There is no moat. Build something amazing and people will use it. Thank you for coming to my TED talk.

Introducing ChatGPT for Dishwashing GPT-6 achieves state-of-the-art results on dishwashing benchmarks for long-running jobs and difficult stains. The Navier–Stokes Millennium Prize Problem is a $1 million challenge about whether the equations describing fluid motion can break down. In this video, I accidentally found a counter-example while trying to optimize my dishwasher. But in reality, OpenAI used 10,000 AI agents to find a proof in 88 hours: Parody of the original GPT-6 Astra ad @OpenAI #ChatGPT_Partner# #chatgpt# Credits: Written and Directed by Joma Co-Writer - Henry Connor Coan IV @coan_henry Production by Dauntlus Studios @dauntlus.studios Producer/Co-Director - Marcus Liew @dauntlus Camera Operator - Amos Lee @amoselijahlee Art Director - Alethea Soo @aletheasoo Art Assistant - Alicia Lim @aliciatkl_ Assistant Editor - GPT-6 Astra Music: Tensions Run High by Soundridemusic

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Whomever thought of the Modretro deserves a raise. Incredibly cool. The console comes with a blank cartridge and you will literally build the game with Codex and load it onto the device. 😏