OpenClaw can now scrape any website without getting blocked - zero bot detection, bypasses Cloudflare natively, 774x faster than BeautifulSoup.
No selector maintenance. No workarounds. Just data.
THIS IS AN UNFAIR ADVANTAGE AND IT'S FULLY OPEN SOURCE.
Nayib Bukele really is the example of "you can just do things." People tell him he can't fix the crime, drops to 1 in 100,000 homicide rating. People tell him El Salvador is poor, buys Bitcoin and dunks on the plebs. People tell him the country is corrupt, impeaches all the judges. It's founder energy. It's amazing what can happen when someone is actually allowed to ship.
The elephant in the room:
Alphabet, Amazon, Meta, Microsoft, and OpenAI alone have announced $800 BILLION in commitments for new data centers in 2025.
Meanwhile, electricity prices are up +35% since 2022.
With nuclear power 10+ years away, how will we meet electricity demand?
An interesting interview with a Former $AMD employee on $NVDA, $AMD, ASICs, and the DeepSeek ramifications:
1. He thinks the gap between $NVDA and $AMD is constant. The problem for $AMD is in its software capabilities and $NVDA's entrenchment with CUDA. $AMD has focused heavily on software in the last five years; changes are visible, but it still hasn't caught up to $NVDA.
2. Even though $AMD has »CUDA translators« the problem he sees is latency. When you have a CUDA-optimized code that needs to go through a translator, it is not efficient, and you have latency and other problems. He gives the example of having x86 translators on ARM. Despite having x86 translators to ARM, you still don't have $ARM chips, which are low power and better performance in data centers because the problem is the clunkiness of the translator.
3. He thinks an advantage $AMD might have in the future is that it has both the GPU and CPU in-house, so they can do iterations in one cycle rather than wait for two cycles.
4. He doesn't see a reason for demand for chips to slow down because of DeepSeek. Training today is limited by power; it is not limited because we don't know how to train better. If the training mechanism changes and you can do 10x the amount of training with the same amount of hardware, then your training models will get more complex rather than you settling for fewer chips, because you want to live with whatever training model you have.
5. He is also critical of custom ASICs for AI. He gives a comparison with the crypto industry, where first for mining GPUs were used, then the industry shifted to ASICs, but then 3 years later went back to GPUs because they became more and more powerful. He doesn't see ASICs taking over GPUs in the next 3-5 years.
AMERICA IS BACK. 🇺🇸
Every single day I will be fighting for you with every breath in my body. I will not rest until we have delivered the strong, safe and prosperous America that our children deserve and that you deserve. This will truly be the golden age of America.
Pitching idea ✅
Recruiting talent✅
Assembling the team✅
Structure✅
Development 👨💻( In-Progress )
Personal Revenge/Goal (Underway) 🚧
Work in silence and let your work make the noise. #Fuckthehaters and #Nonbelievers