ASC

[Cristiano Ronaldo @Cristiano]

Não era o arranque que queríamos, mas isto está longe de ter acabado. Cabeça levantada e foco no próximo jogo.

[Portugal @selecaoportugal]

Juntos com a certeza de que #VaiDarPortugal ❤️‍🔥🇵🇹

#FIFAWorldCup | @433

[Belushi's Farm Oregon @belushisfarmOre]

If you smell cannabis in your neighborhood, here's what to do:

1) Mind your business

[terminally onλine εngineer @tekbog]

it’s never too late to learn about data intensive applications

[Can Vardar @icanvardar]

this is the way

[Branko @brankopetric00]

Vector databases explained for people who just want to understand.

You have 10,000 product descriptions. User searches for "comfortable outdoor furniture."

Traditional database:
- Searches for exact word matches
- Finds products containing "comfortable" OR "outdoor" OR "furniture"
- Misses "cozy patio seating" even though it's the same thing
- Keyword matching is stupid

Vector database approach:
- Convert search into numbers representing meaning: [0.2, 0.8, 0.1, 0.9, ...]
- Convert every product description to similar numbers
- Find products with similar number patterns
- Returns "cozy patio seating" because the numbers are close
- Meaning matching is smart

How it works:

Step 1: Turn text into vectors (arrays of numbers)
- "comfortable chair" becomes [0.2, 0.7, 0.1, 0.4, ...]
- "cozy seat" becomes [0.3, 0.8, 0.2, 0.5, ...]
- Similar meanings = similar numbers
- Uses AI models like OpenAI embeddings

Step 2: Store vectors efficiently
- Traditional database: Stores text
- Vector database: Stores arrays of numbers per item
- Indexes them for fast similarity search
- Optimized for "find similar" not "find exact"

Step 3: Search by similarity
- User query: "outdoor furniture"
- Convert to vector: [0.3, 0.6, 0.2, 0.8, ...]
- Find closest vectors using math (cosine similarity)
- Returns items ranked by similarity score

Use cases:
- Product search that understands intent
- Documentation search that finds relevant answers
- Recommendation engines
- Chatbots that find similar questions
- Anomaly detection

Popular vector databases:
- Pinecone: Managed, easy, expensive
- Weaviate: Open source, feature-rich
- Milvus: Fast, scalable, complex
- pgvector: Postgres extension, simple
- Qdrant: Fast, Rust-based

Controversial take: You don't need a vector database for most projects. Start with Postgres + pgvector extension.

Vector databases are great for scale. For under 1 million vectors, your regular database with a vector extension works fine.

[fan @NoodleHairCR7]

SAY NOTHING JUST RT.

[Ring Journey @RingJourney]

I’m devastated for Ciryl Gane. He was in control, landing at will and busting up Tom Aspinall’s face. Watching the replay, those fingers barely grazed the eye. It looked like Aspinall took the safe way out. The UFC needs to stop pushing narratives just to please the UK crowd☝🏻

[ACD MMA @acdmma_]

Tom Aspinall’s nose is bloody and he’s already breathing with his mouth wide open in round 1 #UFC321

[ASC @ASC7917]

@joinmaat @DanBochman 😂

[Legendary @Legendaryy]

nobody is an atheist at 50x leverage

best marketing ive seen in a long time lol

[JohnRocker @itsJohnRocker]

ALL
CHARLIE
KIRK
DID
WAS
HAVE
A
RESPECTFUL
DIALOGUE
WITH
PEOPLE
HE
DISAGREED
WITH

[UF @UtdFaithfuls]

Solskjaer — Played exciting football. Suddenly looked lost and got sacked.

Ten Hag — Successful at Ajax and one of the most exciting coaches in Europe. Came to United, looked lost, and got sacked.

Amorim — Successful and exciting coach at Sporting. Looks lost, and we know what happens next.

Mourinho — Serial winner. Came to United and said finishing second was one of his biggest career achievements.

I have no idea, but there's obviously a reason why good managers keep failing at United. It can't entirely be their faults that we keep seeing the same patterns.

Just like we say about players, Man Utd is also becoming a graveyard for good managers.

[ASC @ASC7917]

@tragicbirdapp 😂

[❇️ @isthiseshaan]

Get your $aura up.

[smith(fan)🦁 @RMAsmithayo7sui]

throwback to when a marcelo crossing to cristiano ronaldo was equivalent to a penalty 🕊️https://t.co/AgQDTXPzze

[ASC @ASC7917]

@TheNassrZone Bruno 😂

[Freddy🇩🇪 @FreddyLA7]

Portugal have reached four finals in their entire history.

This was Ronaldo in the four semifinals that lead to those finals:

[MS 🇸🇪 @madridistaswe1]

”Nations league will decide the ballon d’or winner between me & Dembele”

Meanwhile 40 year old Ronaldo: