O²

AT14.17SE15.24.0722.29.0722
▪︎vivet ~ amare ~ risu • relinquens mox

[O² @iamlami_]

lost..

[O² @iamlami_]

Bargaining

[Numan @Numan_Ai12]

DELETING YOUR BROWSING HISTORY DOESN'T DELETE YOUR BROWSING HISTORY. GOOGLE KEEPS ITS OWN COPY, TIED TO YOUR ACCOUNT, ON A PAGE MOST PEOPLE HAVE NEVER OPENED. HERE'S HOW TO WIPE ALL OF IT:

[MrBanks💰 @Mrbankstips]

Cancer is a big problem in our society and it almost seems like anyone can get it no matter how careful you are, but you can also do some things to protect yourself and loved ones.

Cut down:
• Charred suya, the black bits, processed meat, sausages and hot dogs used in shawarma etc
• Mouldy groundnut, maize, egusi
• Reused frying oil
• Sniper-preserved beans, formalin fish
• Alcohol (shayo sweet but think about the long term complications) and smoking
• Firewood & generator smoke indoors
• Skin lightening creams

Also do this:
• Test for Hepatitis B and vaccinate if negative, biggest cause of liver cancer in our society. Test for Hep C too (no vaccine, but it’s curable now with treatment)
• HPV vaccine + screening for the women you love, the biggest cause of cervical cancer in our society, and a rising cause of throat cancer
• Grill beside the coals, not over them

Protect yourself. Protect your family.

[O² @iamlami_]

@tobyasky lines dey cry 😂😂

[SANTAN @Santandave1]

IM RAPPING AGAIN!

[O² @iamlami_]

@effxzzzyy why this kind of comparison? lol
an ipad speaker sounds better than the HP speakers

[Hridoy Reh @hridoyreh]

📂 SaaS Stack
┃
┣ 📂 Frontend
┃ ┣ 📂 React
┃ ┣ 📂 NextJS
┃ ┣ 📂 Vue
┃ ┣ 📂 TailwindCSS
┃ ┗ 📂 Shadcn UI
┃
┣ 📂 Backend
┃ ┣ 📂 NodeJS
┃ ┣ 📂 Django
┃ ┣ 📂 Laravel
┃ ┣ 📂 FastAPI
┃ ┗ 📂 Express
┃
┣ 📂 Database
┃ ┣ 📂 PostgreSQL
┃ ┣ 📂 MySQL
┃ ┣ 📂 MongoDB
┃ ┣ 📂 Redis
┃ ┗ 📂 Supabase
┃
┣ 📂 Auth
┃ ┣ 📂 Clerk
┃ ┣ 📂 Auth0
┃ ┣ 📂 Firebase Auth
┃ ┣ 📂 Supabase Auth
┃ ┗ 📂 NextAuth
┃
┣ 📂 Payments
┃ ┣ 📂 Stripe
┃ ┣ 📂 Paddle
┃ ┣ 📂 Dodo Payments
┃ ┣ 📂 Lemon Squeezy
┃ ┗ 📂 Polar
┃
┣ 📂 Emails
┃ ┣ 📂 Resend
┃ ┣ 📂 SendGrid
┃ ┣ 📂 Mailgun
┃ ┣ 📂 Postmark
┃ ┗ 📂 Amazon SES
┃
┣ 📂 Storage
┃ ┣ 📂 AWS
┃ ┣ 📂 Cloudflare
┃ ┣ 📂 Google Cloud Storage
┃ ┣ 📂 Supabase Storage
┃ ┗ 📂 Uploadcare
┃
┣ 📂 Deployment
┃ ┣ 📂 Vercel
┃ ┣ 📂 Netlify
┃ ┣ 📂 Railway
┃ ┣ 📂 Render
┃ ┗ 📂 AWS
┃
┣ 📂 Domains and DNS
┃ ┣ 📂 Namecheap
┃ ┣ 📂 Hostinger
┃ ┣ 📂 Cloudflare DNS
┃ ┣ 📂 Google Domains
┃ ┗ 📂 SiteGround
┃
┣ 📂 Analytics
┃ ┣ 📂 Google Analytics
┃ ┣ 📂 Plausible
┃ ┣ 📂 PostHog
┃ ┣ 📂 Mixpanel
┃ ┗ 📂 DataFast
┃
┣ 📂 Monitoring
┃ ┣ 📂 Sentry
┃ ┣ 📂 LogRocket
┃ ┣ 📂 Datadog
┃ ┣ 📂 NewRelic
┃ ┗ 📂 UptimeRobot
┃
┣ 📂 DevOps
┃ ┣ 📂 Docker
┃ ┣ 📂 Kubernetes
┃ ┣ 📂 GitHub Actions
┃ ┣ 📂 CI CD
┃ ┗ 📂 Terraform
┃
┣ 📂 Search
┃ ┣ 📂 Algolia
┃ ┣ 📂 Meilisearch
┃ ┣ 📂 Elasticsearch
┃ ┣ 📂 Typesense
┃ ┗ 📂 OpenSearch
┃
┣ 📂 AI Integration
┃ ┣ 📂 OpenAI API
┃ ┣ 📂 Anthropic API
┃ ┣ 📂 Replicate
┃ ┣ 📂 HuggingFace
┃ ┗ 📂 Gemini API
┃
┣ 📂 Integrations
┃ ┣ 📂 Zapier
┃ ┣ 📂 Make
┃ ┣ 📂 n8n
┃ ┣ 📂 Pabbly
┃ ┗ 📂 Webhooks
┃
┣ 📂 Security
┃ ┣ 📂 SSL
┃ ┣ 📂 Cloudflare
┃ ┣ 📂 WAF
┃ ┣ 📂 Rate Limiting
┃ ┗ 📂 Secrets Management
┃
┣ 📂 Marketing
┃ ┣ 📂 Search Console
┃ ┣ 📂 Outrank
┃ ┣ 📂 Buffer
┃ ┣ 📂 Analytics
┃ ┗ 📂 Kit
┃
┗ 📂 Customer Support
┣ 📂 Intercom
┣ 📂 Crisp
┣ 📂 Zendesk
┣ 📂 Tawk
┗ 📂 HelpScout

[CryptoSoulz @SoulzBTC]

Every Trading Strategy Explained in 6 Minutes

0:00 - Fibonacci Retracements
0:27 - Chart Patterns
1:01 - Elliot Wave
1:51 - FVG
3:06 - Support & Resistance
5:01 - Volume
5:22 - Supply and Demand
5:50 - Break of Structure
5:58 - Change of Character

[Anish Moonka @anishmoonka]

You’ve never touched anything in your life. Not your phone. Not your morning coffee. Not the person you love.

Every atom in your body is 99.9999999999999% empty space. If the core of an atom were the size of a marble, the nearest electron would be all the way out in the parking lot of a football stadium. Everything in between is empty.

We’ve known this since 1911. A physicist named Ernest Rutherford fired tiny particles at a sheet of gold foil expecting them all to pass right through. Most did. But about 1 in 8,000 bounced straight back at him. He said it was like firing a cannon at tissue paper and having the shell come back and hit you. That one result proved every atom is almost entirely void, with all its weight crammed into a core 100,000 times smaller than the atom itself.

So when you sit in a chair, you’re not actually sitting on it. The electrons in your body are pushing against the electrons in the chair. Same force that makes two magnets resist each other when you flip one around. You’re floating above the surface, separated by a gap about 10,000 times thinner than a sheet of paper. Every handshake is two invisible clouds of electrons pressing against each other without ever merging.

Remove all that empty space from every atom in every human on Earth, and 8 billion people compress down to a single sugar cube. It would weigh billions of tons and fall straight through the floor, through the crust, all the way to the center of the Earth. Same density as a neutron star.

But the tweet gets one thing a little wrong. Whether atoms “touch” depends on how you define touch. Philip Moriarty, a physicist at the University of Nottingham who literally pushes individual atoms around with a needle for a living, says contact does happen at the atomic level. It’s the point where the pull between atoms balances the push. And when you eat food, your body breaks those molecules apart and chemically bonds with them, atoms merging across boundaries. That’s real contact.

So what you feel when you hold someone’s hand isn’t skin on skin. It’s the same force that holds together every molecule in every star, pressing your electrons against theirs. You’ve never made contact the way your brain pictures it. What’s actually happening is stranger and honestly way cooler.

[Andrej Karpathy @karpathy]

Software horror: litellm PyPI supply chain attack.

Simple `pip install litellm` was enough to exfiltrate SSH keys, AWS/GCP/Azure creds, Kubernetes configs, git credentials, env vars (all your API keys), shell history, crypto wallets, SSL private keys, CI/CD secrets, database passwords.

LiteLLM itself has 97 million downloads per month which is already terrible, but much worse, the contagion spreads to any project that depends on litellm. For example, if you did `pip install dspy` (which depended on litellm>=1.64.0), you'd also be pwnd. Same for any other large project that depended on litellm.

Afaict the poisoned version was up for only less than ~1 hour. The attack had a bug which led to its discovery - Callum McMahon was using an MCP plugin inside Cursor that pulled in litellm as a transitive dependency. When litellm 1.82.8 installed, their machine ran out of RAM and crashed. So if the attacker didn't vibe code this attack it could have been undetected for many days or weeks.

Supply chain attacks like this are basically the scariest thing imaginable in modern software. Every time you install any depedency you could be pulling in a poisoned package anywhere deep inside its entire depedency tree. This is especially risky with large projects that might have lots and lots of dependencies. The credentials that do get stolen in each attack can then be used to take over more accounts and compromise more packages.

Classical software engineering would have you believe that dependencies are good (we're building pyramids from bricks), but imo this has to be re-evaluated, and it's why I've been so growingly averse to them, preferring to use LLMs to "yoink" functionality when it's simple enough and possible.

[Deep Learning Indaba @DeepIndaba]

Applications for #DLI2026 are officially OPEN!

We are excited to open applications for the annual meeting of the African machine learning and AI community: The Deep Learning Indaba 2026 in Lagos, Nigeria!

⏳ Deadline: 29 March 2026

Apply here: https://t.co/G44imR08Kz
👉 Details: https://t.co/sWI4TgPFer

#DLI2026 #Indaba2026

[O² @iamlami_]

@AyandaYandiey wdym you let him overtake you???😭

[Stacy Muur @stacy_muur]

https://t.co/ifWD4c2hJN

[O² @iamlami_]

@sisiolojuede @MissRozapepper you gettt

[Tips Excel | AI Productivity @gudanglifehack]

STOP telling ChatGPT "Write like a Human"
STOP telling ChatGPT "Humanise this"
STOP telling ChatGPT "Humanise that"

Bad prompt = Bad result

These prompts are the best 👇

[PortHarcourt Sailor @PHSailor1]

This is my new video on YouTube about how Nigeria went from having 24 international merchant ships in 1964 to none by 2026. The decline was largely driven by corruption and embezzlement. Many of the ships were eventually seized in foreign ports due to unpaid debts.

Here’s the link: https://t.co/S2SXJ8Tm3G

I really wish this video will go viral. If this comes across your timeline, please share.

[Ankit Jxa @kingofknowwhere]

> be data scientist
> boss gives 5TB of raw .txt files. (In interview always ask file format btw)
> "just do some word counts and searches, anon"
> MFW it would take 3 years to grep this on his t3 micro mini aws
> time to go full autist and achieve maximum throughput
The "Ascended" Data Pipeline
> Step 1: The Great Partitioning
> don't just "read" the files because byte io streams will cry
> use pyarrow.dataset to scan the disk
> fragment the raw text into 128MB Parquet chunks
> optimise for L3 caching and NVMe sequential read speed
> partition by date/source so the OS doesn't cry
> Or partition by random (non English words)
> Step 2: The Information Theory Play
> take a 1% statistical sample of the whole 5TB
> build a global FSST (Fast Static String Taxonomy) dictionary
> global dictionary for high-cardinality terms
> identify the common prefixes/suffixes for trie storage
> language entropy into 1-byte symbols
> A LOUDS Trie uses only 2.14 bits per node.
> You can then run POPCNT at O(1)
> Step 3: The Ingestion (The "Warm-up")
> spin up every CPU core you own
> pq.ParquetWriter with dictionary_encoding=True
> convert raw strings into integer keys pointing to the FSST Trie
> attach a Bloom Filter to every Row Group
> if the word "abcd" isn't in the filter, the CPU won't even look at the data
> key based counting is easy but we take one step ahead
> Step 4: Memory Mapping (Arrow fs "No-Copy" Hack)
> set mmap=True in the PyArrow scanner
> OS kernel handles the data
> RAM usage stays at 500MB while processing TBs
> physical disk bytes are mapped directly to virtual address space
> ZERO. COPIES. MADE.
> Step 5: More optim: The GPGPU Option
> standard Python is for children
> pipe the Arrow Buffers directly to NVIDIA cuDF via GPUDirect Storage
> bypass the CPU and System RAM entirely
> NVMe -> PCIe -> VRAM
> Step 6: The Calculation (The "Sigma" Move)
> bit-sliced parallel search on the GPU
> 5,000+ CUDA cores performing integer comparisons on the FSST keys
> search O(1) instead of O(N)
> word counts happen at 40GB/sec
> finish the 5TB task before your coffee gets cold
> Step 7: CPU "SIMD" cope-poor people pathway
> if you're poor and don't have a GPU
> use AVX-512 bit-slicing in C++
> process 64 words in a single clock cycle on one core
> still faster than 99% of "Big Data" engineers

[ABIODUN | TIGA Autos. @_Tiga_b]

These numbers always come in handy, especially if you're a dealer. Anytime a car I sell going out of Lagos is harassed by the police, I immediately call their PRO and they act right. Two days ago, some men claiming to be SWAT stopped a car in Ibadan. As soon as they heard I was going to call the @OyoPoliceNG PRO, they left the driver alone before I even finished the call.

If you know you're in the right and there's no mistake on your part, don't rush follow them to the station and call their boss.

[Chioma Amadi @Chioma__Amadi]

I can’t remember the last time I agreed with everything an article said.

But if you’re actively job hunting, you might want to see this.

Implement it religiously, and you’ll be glad you did.

[O² @iamlami_]

if this story is true, dem suppose def Einstein 💀

[Imtiaz Mahmood @ImtiazMadmood]

One of Einstein’s students asked him: “What does logic mean?”

Einstein said: “I will answer you with a question.”

“Suppose two workers enter a chimney to clean it. One comes out with a dirty face and the other with a clean face. Who will go wash their face?”

The student immediately and without hesitation replied, “Of course, the one with the dirty face.”

Einstein said: “Your answer is incorrect. The one who will wash their face is the one with the clean face, because he looked at his colleague’s face and assumed that his own face was as dirty as his colleague’s. The one with the dirty face will not wash his face, thinking it is clean like his colleague’s.”

The student said: “That is correct and logical.”

Einstein replied: “No, it is not correct, because the question itself is illogical. It is not logical for two men to enter the same chimney at the same time and for one to come out clean and the other dirty.”

In a few words, logic itself can collapse, so sometimes the problem is not in the answer but in the flawed question itself.

- @GlobalIJournal