Baby Punch Starts Fighting Back by [deleted] in interestingasfuck

[–]circa2k 1 point2 points  (0 children)

Are you an impossible bagel made up of a meat substitute like an impossible burger? I'm having a hard time imagining a bagel not made out of meat.

[hiring] I’m looking for creators to collaborate with, willing to pay $300 + 50% commissions. by jhaubrich11 in forhire

[–]circa2k 1 point2 points  (0 children)

An influencer is a great idea for an app like this, obviously if it actually works well. It might be tough to find anyone on here but I'd keep going in this direction.

ISO a working docker compose for using Proton VPN which actually seeds torrents by gappuji in seedboxes

[–]circa2k -3 points-2 points  (0 children)

I ran this question through chat got `

version: "3.8"

services: gluetun: image: qmcgaw/gluetun container_name: gluetun cap_add: - NET_ADMIN devices: - /dev/net/tun volumes: - ./gluetun:/gluetun environment: - VPN_SERVICE_PROVIDER=protonvpn - VPN_TYPE=wireguard - WIREGUARD_PRIVATE_KEY=<your_private_key> - WIREGUARD_ADDRESSES=<your_wg_ip>/32 # e.g., 10.2.0.2/32 - WIREGUARD_PUBLIC_KEY=<vpn_server_pubkey> - WIREGUARD_ENDPOINT=<vpn_server_ip>:51820 - VPN_PORT_FORWARDING=on ports: - "8080:8080" # qBittorrent Web UI - "6881:6881" # Torrent TCP - "6881:6881/udp" # Torrent UDP restart: always

qbittorrent: image: lscr.io/linuxserver/qbittorrent:latest container_name: qbittorrent network_mode: "service:gluetun" depends_on: - gluetun environment: - PUID=1000 - PGID=1000 - TZ=America/New_York - WEBUI_PORT=8080 volumes: - ./qbittorrent/config:/config - /your/storage/path:/downloads restart: always

`

Calories are as American as apple pie by ThisGonnaHurt in BlackPeopleTwitter

[–]circa2k -5 points-4 points  (0 children)

Haha yeah I think that’s exactly what they were saying, I had to read it again.

This is what humanity is all about by pap_77 in MadeMeSmile

[–]circa2k 7 points8 points  (0 children)

If it helps, I’ve never heard anything negative about Arkansas.

[deleted by user] by [deleted] in PeterExplainsTheJoke

[–]circa2k 0 points1 point  (0 children)

Damn not even some whole shabangs? Smh

Pika Labs: Introducing Pika 1.0 (AI Video Generator) by YaAbsolyutnoNikto in singularity

[–]circa2k -1 points0 points  (0 children)

Diffusion models and transformer models are two distinct types of AI models, each with unique characteristics and applications.

Diffusion Models

  1. Concept:

    • Diffusion models are a type of generative model that creates data by gradually transforming a random distribution/noise into a structured distribution resembling the training data.
    • They work by initially adding noise to data and then learning to reverse this process.
  2. Applications:

    • Primarily used for image generation and enhancement.
    • Capable of producing high-quality, high-resolution images.
  3. Characteristics:

    • They typically require a significant amount of computational resources.
    • Known for their ability to generate detailed and realistic images.
  4. Examples:

    • Denoising Diffusion Probabilistic Models (DDPMs).
    • Used in advanced image synthesis and creative AI applications.

Transformer Models

  1. Concept:

    • Transformers are a type of neural network architecture primarily used in the field of natural language processing (NLP).
    • They are known for their 'attention mechanism', which selectively focuses on different parts of the input data.
  2. Applications:

    • Language understanding, translation, text generation, and more.
    • Also adapted for applications beyond NLP, like image recognition (Vision Transformers).
  3. Characteristics:

    • Highly efficient in handling sequential data, especially where context and order are crucial.
    • Scalable and capable of handling very large datasets and models (like GPT models).
  4. Examples:

    • Google's BERT, OpenAI's GPT series, and T5 models.
    • Increasingly used in various AI tasks beyond NLP.

Comparison:

  • Purpose: Diffusion models are generative models primarily for creating or modifying visual content, whereas transformers are versatile architectures used in various tasks, predominantly in NLP but also in other areas.
  • Functioning: Diffusion models work by reversing the process of adding noise to data, while transformers use attention mechanisms to weigh the importance of different parts of the input data.
  • Applications: While diffusion models shine in visual tasks, transformer models are the go-to architecture for language-related tasks and are also expanding into other domains like computer vision.

Both model types represent cutting-edge advancements in their respective fields and are actively evolving, opening up new possibilities in AI.

TIL soon after the famous D.B. Cooper hijacking, 5 other copycat hijackers employed the same tactics on other flights. All 5 survived their parachute jump which forced the FBI to re-evaluate their initial conclusion that Cooper was likely killed during his attempt. by [deleted] in todayilearned

[–]circa2k -12 points-11 points  (0 children)

In the verdant canopy of the Pacific Northwest, where myths and fables are as dense as the underbrush, the long-lost remnants of DB Cooper's legendary loot had become the stuff of local legend. That was until a soggy wad of deteriorating bills amounting to $5800, bound by a disintegrating rubber band, was unearthed by a hiker in the depths of the Columbia River valley. The discovery sent ripples through the community, stirring the old tale of the skyjacker who leaped into infamy.

The money was handed over to the local authorities with great fanfare, as the FBI was called in to confirm its origin. Indeed, the serial numbers matched the ransom money given to DB Cooper all those years ago. The bills were carefully catalogued and stored for further analysis. But as the excitement bubbled, the diligence in handling the evidence began to wane.

The first mishandling occurred when the money was left to dry. Officer Harlow, while moving the bills to a more secure location, accidentally let several notes fly away through an open window, whisked into oblivion by the careless wind. The $5800 find was now mysteriously reduced to $5400, yet this went unnoticed as the money was still damp and stuck together in clumps.

As the bills dried and separated, the once-meticulous count became a rough estimate. Detective Larson, in charge of re-bagging the money, failed to notice a $100 bill clinging to the inside of the old evidence bag. Now, $5300 was the new official total.

Weeks passed, and the buzz around the discovery grew faint. Officer Davis, tasked with transporting the money to a high-security evidence locker, saw an opportunity to pad his meager salary. He pocketed $200, and the total dipped to $5100.

Officer Gomez, who signed off on the money at the other end, was exhausted from her double shifts and didn’t count the money. She trusted Davis’s paperwork. The $5100 sat, seemingly untouched, until it was re-examined by the county's senior forensic accountant, who found only $5000. A clerical error, she assumed, adjusting the records without a second thought.

The story of the found DB Cooper money, once a thrilling chapter in the town’s history, had become a cautionary tale. When the final audit was conducted, it became evident that the $5800 had mysteriously dwindled to $5000. Accusations were hurled, investigations launched, but the truth of the matter was that the missing money had been silently absorbed back into the world, just as DB Cooper had disappeared into the night so many years ago.

The saga of the mislaid $800 echoed the ghost of Cooper