#paidtolivefulltime

Living fulltime, having fun the world over.

[Random Videos @Randomvideos107]

Are these the “good” cops they keep telling us about? #police #cops #policeofficer #law #audit

[Scene stealer @Ikechukwuol1j3]

Who is the fastest being in history 🎥🎥

[The Cake Lady @got_cake]

Have you ever wondered if you can drink the guttation fluid or sap found in some plants?

[Herbalisque @Herbalisque]

🎥 Don’t take my word for it—watch this below and see for yourself! 👇

[Loud Outside @LoudOutside]

Real Tarzan gets wrecked by a wild animal that was clearly not in the mood

[Antid @antisadh]

SONY SHIPS THIS APU IN A $200 PS5. BITCOIN OPERATIONS DUMPED IT ON EBAY FOR $40. HE 3D PRINTED A CASE OVERNIGHT AND KILLED $439 A MONTH IN ANTHROPIC AND OPENAI BILLS

00:34 he turns the board over and says "this was actually meant for bitcoin mining originally, and this uses ps5 adjacent hardware for the apu"

$80 bc250 off ebay -> one 8 pin connector, no pcie, no motherboard -> $50 flex itx 500w psu -> 20 hour ASA print for the case -> blow four years of mining dust out with an air compressor -> 16gb gddr6 unified, ollama up in 4 minutes

sony sold 117 million ps5s on this silicon, bitcoin operations bought the mining variant by the pallet, ethereum's merge stranded all of it, and now the same oberon apu that renders spider-man runs a local coding model for the price of a dinner

the honest part: it arrived filthy, the compressor barely touched the dust, and you need a 3d printer before the board does anything at all

$80 amd bc250 + $50 flex itx 500w + 20h ASA print + oberon apu with 16gb gddr6 + ubuntu + ollama

watch and save it, then kill your $439 stack this weekend, kimi does the same work at $19 flat and the whole map is in the article below

[Precious 💫 @Precious7310]

🎬 After 7 years of marriage, he discovered a shocking secret about his wife and another man.💔

[Avi Chawla @_avichawla]

DevOps vs. MLOps vs. LLMOps, clearly explained:

Many teams are trying to apply DevOps practices to LLM apps.

But DevOps, MLOps, and LLMOps solve fundamentally different problems.

DevOps is software-centric. You write code, test it, and deploy it. The feedback loop is straightforward, i.e., does the code work or not?

MLOps is model-centric. Here, you're dealing with data drift, model decay, and continuous retraining. The code might be fine, but the model's performance can degrade over time because the world changes.

LLMOps is foundation-model-centric. Here, you're typically not training models from scratch. Instead, you're selecting foundation models and then optimizing through three common paths:

- Prompt engineering
- Context/RAG setup
- Fine-tuning

But here's what really separates LLMOps: The monitoring is completely different.

In MLOps, you track data drift, model decay, and accuracy.

In LLMOps, you're watching for:

- Hallucination detection
- Bias and toxicity
- Token usage and cost
- Human feedback loops

This is because you can't just check if the output is "correct." You need to ensure it's safe, grounded, and cost-effective.

The evaluation loop in LLMOps also feeds back into all three optimization paths simultaneously. Failed evals might mean you need better prompts, richer context, OR fine-tuning.

So it's not a linear pipeline anymore.

One more thing: prompt versioning and RAG pipelines are now first-class citizens in LLMOps, just like data versioning became essential in MLOps.

And the ops layer you choose should match the system you're building.

If you want to go deeper into LLMOps, I wrote a full LLM engineering roadmap a while back.

It walks through the eight pillars of building LLM systems, starting at prompt engineering and ending at observability and safety, with free and open-source resources attached to each one.

You can read it below.

[Official Real Empire🎬 @SofiaJames51562]

She could see the hidden side of people’s love lives...👀

[Official Real Empire🎬 @SofiaJames51562]

The revenge plan. 👀🔥

[Aisar @aisarcore]

A Massachusetts man bet $12,950 on a hole DraftKings accidentally created in its own system. It paid him $934,147.83. DraftKings tried to cancel most of it. Regulators said no.

– On October 15, 2025, during Game 3 of the MLB ALCS between the Toronto Blue Jays and Seattle Mariners

– A DraftKings trader misclassified Blue Jays outfielder Nathan Lukes as a "non-participant" in the company's internal trading system.

– That error disabled the safeguard meant to stop customers from stacking correlated versions of the same bet into one parlay.

– It meant a bettor could combine Lukes' hit totals, 5+, 6+, 7+, and 8+ hits in the series, all inside a single ticket, each leg priced as if it were independent.

– A Massachusetts customer found the gap and placed 27 parlays totaling $12,950, several of them padded further with unrelated college football and NFL favorites.

– Lukes finished the seven-game series with nine hits. Twenty-four of the 27 parlays hit.

– DraftKings owed him $934,147.83.

– DraftKings froze the tickets and asked the Massachusetts Gaming Commission for permission to void most of it

– Offering to pay roughly $96,000 instead and calling the bettor's actions "unethical."

– On December 18, 2025, the commission rejected that argument outright, noting the error was entirely internal to DraftKings, not caused by any outside data feed.

– One commissioner put it plainly: "It's the cost of doing business."

– The vote was unanimous, 5-0. DraftKings was ordered to pay the full $934,147.83.

He found a hole DraftKings built into its own system, bet directly into it, and won. DraftKings tried to rewrite the outcome after the fact. Regulators told them the mistake was theirs to keep.

[Subbmannnn @Avinash54392]

Sorry To say But i like the Original One .

[Flint @flintiko]

HE WAS MAKING $3 AN HOUR BEHIND A 7-ELEVEN COUNTER WHEN HE FOUND THE ONE INPUT EVERY GAMBLER THROWS IN THE BIN AND IT TURNED INTO CLOSE TO $1 BILLION

His model was mathematically flawless and it lost $120,000 of a $150,000 stake in its first season.

His name is Bill Benter. He read a book about blackjack on his night shifts, went to Las Vegas in 1979, and counted cards well enough to pull around $80,000 a year until the casinos blacklisted him in 1984. Barred from every table in town, he moved to Hong Kong with a computer and started typing race results in by hand. His program scored more than 120 details on every horse. It still bled.

What was missing was the thing he had been treating as the enemy. The public's own odds.

A million people bet on those races. Between them they saw what no database holds: a horse sweating in the paddock, a jockey riding hurt, a trainer nobody trusts. Benter stopped trying to outguess that crowd and wrote its opinion into his model as another variable. Then he played only the races where his number and the crowd's number came apart. Everything else he skipped.

First full year after that change: $600,000. The 1990-91 season: $3 million. Career: close to a billion dollars.

"I'm kind of a one-trick pony."

On 6 November 2001 he put HK$1.6 million across 51,000 combinations and hit a jackpot worth HK$118 million. He never collected it. A letter reached the Jockey Club telling them to give the money away.

Watch a man leave sixteen million dollars sitting on a counter. Almost everyone would have cashed that ticket the same afternoon, and that is precisely why almost nobody gets the billion behind it.

[Earth_Wanderer @earth_tracker]

To all the people who don’t allow cats in the yard…..this one’s for you.

[T̶Ø̶Ø̶F̶🦷 @FrontToof]

⛩️

[SOLEX @warrior_yungjun]

Marvel's darkest reality ends with a twist, a version of the Silver Surfer nobody expected. #comics

[XLadyGlow @xladyglow]

Wait for the last part🫵 😳🥰✨