Simon()

19.4K posts

Simon() banner
Simon()

Simon()

@dickson_oche

-Software | Data | Building Systems | Member @Cohere_Labs Open Science Community | Rx

👨🏽‍💻 Katılım Haziran 2017
1.7K Takip Edilen1.7K Takipçiler
Simon() retweetledi
OjieMusic
OjieMusic@TweetOjie·
There’s a phase you get to in life life, all those hymns you sang in your childhood as mere songs , starts making total sense Because what a friend we really have in Jesus ?
English
187
8.1K
28.8K
360.8K
Simon() retweetledi
𝑱𝒐𝒔𝒉_0̷𝒙
𝑱𝒐𝒔𝒉_0̷𝒙@joshsupremacy_·
I’m still actively onboarding and tasking accounts on outlier✅ If you have Aether, Whitebeard, Blackbeard, Almanac or Voice Mission, send a dm let’s work together. I do quality job and max out hours while protecting the acc from flags or bans.
𝑱𝒐𝒔𝒉_0̷𝒙 tweet media𝑱𝒐𝒔𝒉_0̷𝒙 tweet media
English
5
2
4
569
Simon() retweetledi
𝑱𝒐𝒔𝒉_0̷𝒙
𝑱𝒐𝒔𝒉_0̷𝒙@joshsupremacy_·
Do you need any help with your OUTLIER project? I offer full-service: ✅ Onboarding and Assessments ✅ Account Management and Tasking I handle Whitebeard, Blackbeard, Voice Mission, Almanac, & Aether. If you need help with any or to create acc, DM me! 📥 Evidence dey!✅
𝑱𝒐𝒔𝒉_0̷𝒙 tweet media𝑱𝒐𝒔𝒉_0̷𝒙 tweet media𝑱𝒐𝒔𝒉_0̷𝒙 tweet media𝑱𝒐𝒔𝒉_0̷𝒙 tweet media
English
3
4
12
1.9K
Simon() retweetledi
Diekola
Diekola@ChrisAleji·
Pharma West Africa Conference 2026 ✨
Diekola tweet mediaDiekola tweet media
English
4
14
206
10K
Simon() retweetledi
klöss
klöss@kloss_xyz·
“you need to be unemployed, locked in 24/7, and on 3 hrs of sleep a day just to keep up with all these Claude updates”
klöss@kloss_xyz

x.com/i/article/2036…

English
49
145
1.9K
295.6K
Simon() retweetledi
Anish Moonka
Anish Moonka@anishmoonka·
Part 2. The engineering side. So the brain is absurdly efficient. Naturally, everyone is now trying to copy it. Three separate races are happening at once, and they barely overlap. Race 1 is developing computer chips that work like neurons rather than traditional processors. Normal computers waste most of their energy shuttling data between two separate places: the part that stores information and the part that does calculations. Your brain doesn't do this. Every connection point stores memory AND processes information in the same spot. Intel built the largest brain-inspired system to date, called Hala Point. It fits 1.15 billion artificial neurons into a box the size of a microwave oven. On certain tasks, it runs 20 times faster than a human brain. But it still uses 2,600 watts. Compare that to the brain's 20. IBM and BrainChip are running their own versions of this. The gap is closing, but it's still enormous. Race 2 is the one that gets weird. Instead of building chips that imitate neurons, some labs are just using actual living neurons. An Australian startup called Cortical Labs grew about 800,000 human neurons on a silicon chip in 2022, and the neurons taught themselves to play Pong within minutes. No code. No training data. Just cells figuring out a game. In March 2025, they launched a product called CL1, a box that wires lab-grown neurons to electrodes. Costs $35,000. A Swiss company called FinalSpark went further, they host tiny clusters of neurons in the cloud so researchers can rent access over the internet. An Indiana University team built something called Brainware that hit 78% accuracy on speech recognition and cut training time by 90% compared to regular computers. The ethical lines here are genuinely unresolved. Thirty scientists published a joint letter pushing back on claims that these neuron clusters show signs of awareness. Nobody agrees on where the moral boundary is, or even how to measure it. Race 3 is about copying the brain's software rather than its hardware. One reason the brain is so efficient is that only about 1-1.5% of your neurons fire at any given moment. It's an incredibly sparse system. Most AI today does the opposite. Everything activates, all the time, burning through power. Europe's Human Brain Project (a 10-year initiative that ended in 2023) developed two chips, BrainScaleS and SpiNNaker, that mimic the brain's sparse firing pattern. BrainScaleS uses analog circuits rather than digital ones, the same type of electrical signals that neurons actually use. Early results showed 100x power savings over traditional chips. TDK and the French Atomic Energy Commission are building something called spin-memristors that combine memory and processing in one device, using the same principle the brain uses at the smallest scale anyone's tried so far. I keep coming back to the same thought. We spent decades building AI systems that can beat us at chess, write essays, and generate images. Collectively, they eat gigawatts of electricity. And the answer to making them sustainable might be sitting in the same 1.4 kilograms of wet tissue that led to the problem in the first place.
English
10
74
425
22.9K
Simon() retweetledi
Brian Armstrong
Brian Armstrong@brian_armstrong·
Operating in stealth mode is almost always a mistake. Talk publicly about what you're building. You’ll build momentum, get real feedback, and someone will reach out with the other half of your idea you didn’t realize you were missing.
English
730
654
7.6K
634.5K
Simon() retweetledi
shirish
shirish@shiri_shh·
meanwhile there's a whole world that doesn't care about Al benchmarks or github stars.
English
76
195
3.4K
56.8K
Simon() retweetledi
Victoriano Izquierdo
Victoriano Izquierdo@victorianoi·
In 20 years, vibe coders will look at the Linux kernel repo the way we look at the pyramids. In awe, unable to imagine how they managed to drag all those giant stones and pile them up in the middle of the desert.
English
253
1.6K
17.6K
531.2K
Simon() retweetledi
Karan🧋
Karan🧋@kmeanskaran·
"we used to import tensorFlow to train neural networks."
Karan🧋 tweet media
English
73
414
8.1K
227.9K
Simon() retweetledi
cova
cova@covacut·
to all the names i’ve loved before 🩷
English
266
535
8.1K
105K
Simon() retweetledi
Anish Moonka
Anish Moonka@anishmoonka·
If Claude Code or Codex just one-shotted an app for you, Read this. Now you gotta go through every screen and find the 47 edge cases that break it. Users will do things you never imagined. Then comes auth, database setup, API rate limits, error handling for when the server goes down at 2am. You need analytics to figure out what users actually do vs what you think they do. App Store optimization, screenshots, descriptions, review responses. Privacy policies, terms of service, data compliance. Push notifications that actually work without being annoying. Performance optimization because that smooth demo gets real laggy with real data. State management across the whole app. Caching strategy. Offline support. Responsive design across 15 different screen sizes. Testing on older devices that somehow still exist. CI/CD pipeline so deploys don't eat your weekends. Then users start requesting features you never planned for and suddenly your clean architecture needs a rewrite. The first version is maybe 10% of the actual work. Building is easy. Shipping and maintaining is where it gets real.
CG@cgtwts

pov: Claude one shotted a project i planned to make over several months

English
171
407
6.7K
617.5K
Simon() retweetledi
keshav
keshav@kshvbgde·
when the model starts hallucinating and you need to start from scratch
English
117
340
6.9K
206.3K
Simon() retweetledi
Compound’25
Compound’25@pharmaffinclass·
The Premier School of Pharmacy has finally shown who is King. News reaching us has it that Ogunmakinwa Faith of Ife pharmacy is the new winner of the SYA. In other news, the first and the best provided a candidate who had a negative mark in the competition, while Unilag lagged
Compound’25 tweet media
English
4
34
70
3.2K
Simon() retweetledi
𝐑.𝐎.𝐊 👑
𝐑.𝐎.𝐊 👑@r0ktech·
“It worked on production just like it did on localhost”
English
171
1.7K
21.3K
449.4K
Simon() retweetledi
alli
alli@sonofalli·
anthropic vs openai is like kendrick vs drake but for nerds
English
190
846
8.9K
278.3K
Simon() retweetledi
Claude
Claude@claudeai·
Ads are coming to AI. But not to Claude. Keep thinking.
English
1.7K
4K
50.9K
5.2M