Hong Groyper

bringing tears to my eyes

Locked in for $NVDA earnings 🔥

Google I/O - underwhelming - impression I got was that Demis thinks AGI will require world models - he’s thinking of literally any input - any output models - Omni Flash is a toy video model version of this - give was in that it can simulate realistic physics - Demis’ intention seems to be that Omni will eventually generate anything from construction blueprints to gene sequences - also seems to indicate that Deepmind is constrained by data rather than compute for what they intend to do - hence the TPU sales - rest of Google now shipping their org chart - product surface is disorganized and enormous - they are in the let-a-hundred-flowers-bloom phase - coding has clearly been handed to the Antigravity team - Gemini model team and Gemini App team are jumbled together, seems like the push is for Gemini app to become their personal assistant surface - Google is back.. to being a little disorganized

just pay your workers more ong

Oh my god it scored worse than Composer 2! Not even 2.5! And it cost 4x more to run!!! This might be the worst major lab model drop of all time. Llama 4 tier. Insane.

Breaking: The Trump administration has forever banned the IRS from auditing the taxes of Trump, his family members, and his companies.

I'm sorry for hating on Gemini 3.5 Flash so much but come on, what is this

still more bullish on anthropic overall , not because of karpathy but because who’s backing them. msft backing oai is not as strong as google backing anthropic

bruh

Introducing SpectralQuant.. here to save your KV cache :)

is a heart beat just a cron job?

this

Prediction: SpaceX buys Hermes

anthropic

Three ETFs Targeting the Next AI Infrastructure Bottlenecks The first wave: own the obvious AI leaders. But investors may now need to ask where the bottlenecks are forming. Three ETFs offer a useful framework for this shift: SMH, DRAM, and EUV. Each targets a different layer of the AI infrastructure chain. SMH gives broad semiconductor exposure, DRAM isolates the memory bottleneck, and EUV targets lithography, photonics, and optical infrastructure. SMH is the most institutionalized option. It provides exposure to large semiconductor and semiconductor-equipment companies rather than one narrow choke point. Key holdings include $NVDA at 17%, $TSM at 10%, $AVGO at 8%, $INTC at 8%, $AMD at 7%, $MU at 6%, $TXN at 5%, and $KLAC at 4%. This makes SMH the most natural core holding of the group for investors who want exposure to the full AI hardware stack. It covers GPUs, foundries, custom silicon, CPUs, memory, analog chips, and semiconductor manufacturing tools. The trade-off is lower purity. SMH is not a single bottleneck bet. It is a broad semiconductor ecosystem bet. DRAM is more targeted. It is designed around the AI memory squeeze, with exposure to HBM, DRAM, NAND, and storage demand. The fund is highly concentrated. Its largest positions are SK Hynix at 28.15%, $MU at 27.16%, and Samsung at 19.67%. Together, these companies dominate the global memory supply chain. Smaller holdings such as Kioxia, $SNDK, $STX, $WDC, Nanya, and Winbond add exposure across NAND, SSDs, HDDs, and specialty memory. DRAM is arguably the cleanest expression of the AI memory bottleneck. It is also more momentum-driven and concentrated than SMH, with a higher 0.65% expense ratio. EUV is the most specialized and higher-risk ETF in the group. It focuses on the “light layer” of AI infrastructure: photonics, EUV lithography, optical networking, semiconductor inspection, and precision manufacturing tools. Holdings include $TSM at 9.52%, $ASML at 7.97%, $GLW at 5.19%, $LRCX at 4.98%, $AMAT at 4.84%, $LITE at 4.46%, $CIEN at 4.32%, and $KLAC at 4.07%. AI data centers increasingly face limits around power, bandwidth, packaging, and interconnect speed. Photonics and advanced lithography may become critical as compute demand scales. Framework: SMH = core AI semiconductor exposure DRAM = memory bandwidth and capacity bottleneck EUV = lithography, photonics, and optical infrastructure bottleneck

@vulturetrades join

You know what I’m restarting the $100 to $10,000 challenge. I want everyone to have a fair shot at this. Last time it took me about 5 days, will try to do it faster this time. If you want to follow along, comment below to join Going to lock comments in 24 hours

I was a bit hesitant about showing stuff like this just a month ago 😅 When we started showcasing real-time AI + SDF sculpting, I was afraid professionals would laugh if I showed no effort on the input models. The shape strength slider was also hidden in our first iteration, so I had no choice but to at least try and knock some more interesting shapes together. Now that we're starting to focus on more powerful features and shape strength is finally unlocked, I'm starting to appreciate just playing with simple shapes. Different stages of production have different needs. Sometimes you want full authoring over your creations, while other times you just want to quickly explore new ideas.

nevermind

this is huge

legendary use case