RetroOptions 📈

This recent tech selloff has created many generational buying opportunities.  Here’s 6 of MY favourite stocks to buy on this dip; 1. Nebius $NBIS @ $177 2. Micron $MU @ $848 3. Sandisk $SNDK @ $1,350 4. AMD $AMD @ $460 5. Lumentum $LITE @ $650 6. Bloom Energy $BE @ $215 Come back to this post in 3-6 months, you’ll be glad that you listened.  Don’t miss this generational opportunity AGAIN.

Intel's the one.

hetzner price increase is outrageous I am paying 24.99 for my 8GB server If I want another server now, it is 73.49 This is almost a 3x price increase Any hetzner alternative?

Google cultural rot

We have information that Moonshot AI distilled Anthropic’s Fable for the development of its K3 model. To do this they developed a sophisticated internal platform to conduct large scale distillation against U.S. models, allowing them to quickly switch between multiple methods of access to avoid detection. Moonshot AI has also acquired GB300-equipped servers and has accessed GB300s in Thailand, likely to train its AI models.   The United States strongly supports the free and fair development of AI, including a thriving competitive ecosystem that spans frontier models, specialized systems, open-source frameworks, and open-weight models. Legitimate AI distillation used to create smaller, more efficient models plays a vital role in this open innovation ecosystem. However, large-scale, covert industrial distillation aimed at stealing proprietary U.S. technology and undermining American research is unacceptable.

Many people are asking how did Kimi K3 catch up so fast to Western models? Simply, a frontier model really only requires compute, data and people. There is no magic secret. A few answers to this question 1. Kimi with help from the Chinese government has thousands if not tens of thousands of experts (lawyers, scientists, doctors, programmers.. etc.) making RL env data every day. A frontier model is RLed on “tasks”. Each one of these tasks needs to be created by either a human or an LLM. Claude did not wake up one day knowing how to use say the Github CLI. He learned how to use the Github CLI in an RL env.  Meta is pursuing this exact same strategy with its Applied AI org and IMO it appears to be working. 2. I have said this before regarding GLM 5.2 - Kimi obviously distilled from GPT 5.5 and Claude Opus. This only eliminated their cold start problem in RL, meaning they skipped say some X number of months in cold start RL. The mass number of RL envs created by their experts is still the most crucial part here, and you cannot attribute Kimi’s success to distillation. Distillation only saved them some time. 3. Agentic coding and frontier LLMs significantly accelerated their research. My hunch is they use proxies to access Claude API and GPT API for their own model development. Claude most likely wrote all their training code. This release leads to some very interesting questions. What happens now in a world in which an almost Fable class model is open sourced and free on July 27th? My view is intelligence / software will become very soon close to free. Chip makers and inference providers are big winners from Kimi’s success.

$NFLX Is Netflix running out of ideas to grow revenue? Today, it asked my kid to provide an email for their profile on my family account

"The next trillion-dollar company, ladies and gentlemen." - Jensen Huang on Marvell $MRVL

We're extending Claude Fable 5 access on all paid plans, as well as keeping Claude Code’s weekly rate limits 50% higher, through July 19.

OpenAI has reduced GPT-5.6 Sol's thinking budgets in an effort to make the model more efficient They essentially bumped everyone's reasoning down by 1... so if you were running Sol Extra High, you now have to set it to Max to get the same effort So we basically don't have Max reasoning anymore, how do you feel about these changes? 🤔