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aientity · one source so far

pytorch

for ml engineers, AI startups

Steadydevto
Signal score
5
Live items
2
Trajectory
→ Steady
7-day est. ~8

Why this scored 5

every term, weighted
Velocity+0.0 / 40

Its fastest-moving item, measured against the pace of its own source

Acceleration+11.0 / 25

Whether that velocity is itself speeding up, as a per-hour rate

Cross-source spread+0.0 / 25

How many independent communities its own items come from

Recency+0.0 / 10

Decays to zero over 14 days, counted from when we first saw it

Saturation penalty−6.2 / 30

Subtracted once something is big and old — sized by its biggest item, aged from when we first saw it

Composite4.7

Weights are hand-tuned, not learned — we're calibrating them against realized trends as history accumulates. On an entity's first sighting there's no previous reading to compare against, so acceleration starts from a neutral prior rather than a measurement, and velocity falls back to engagement over its whole lifetime until a second reading exists. Full methodology

Outlook

medium confidence · estimate, not a guarantee

7-day

~8

range 0–20

14-day

~9

range 0–24

30-day

~10

range 0–29

Signal history

7-day window (free)
062

projected trajectory (estimate, not a guarantee)

The evidence

The live items this entity's score aggregates — every community independently talking about it right now. This is the corroboration, shown, not claimed.

  1. 1
    39

    How to Run Turing-Complete Malware in PyTorch's Backward Pass

    Embedding malware in PyTorch backward pass shows new model-level attack vector. · for ML security researchers, ML engineers

    lobstersEmerging 2 · pytorchsecurity4d ago
  2. 2
    37

    I Was Learning PyTorch, Then I Accidentally Started Building My Own AI Training Framework

    Creating a custom training framework exposes limitations in PyTorch for niche AI workloads. · for ml engineers, AI founders

    devtoSteady 4 · pythonai63d ago
  3. 3
    32

    How I make a PyTorch model bit-identical outputs across different GPUs, cuDNN versions, and CPU fallback, with no source of nondeterminism anywhere?

    Deterministic PyTorch outputs across GPUs and CPUs improve reproducibility. · for ml engineers, research scientists

    stackoverflowSteady 3 · pytorchai21d ago
  4. 4
    30

    Building Regression in PyTorch

    Guides building regression models using PyTorch library. · for ml engineers, data scientists

    devtoSteady 2 · pytorchai45d ago
  5. 5
    22

    PSRben/VisionHOPE (image-classification)

    VisionHOPE offers ready-to-use PyTorch models for image classification tasks. · for ml engineers, computer vision researchers

    huggingfaceSteady 3 · pytorchai−10 saturated25d ago
  6. 6
    22

    @sentropic/llm-mesh — Provider-agnostic LLM access runtime SDK for Sentropic.

    Provider-agnostic LLM access · for ai founders

    npmCooling 2 · pytorchai97d ago
  7. 7
    18

    Gemma 4 on a 4 GB GPU in Plain PyTorch: From Out of Memory to Faster Than llama.cpp

    Gemma 4 runs on 4 GB GPU with PyTorch quantization, reducing hardware needs. · for ml engineers, AI startups

    devtoSteadyai2d ago
  8. 8
    18

    PyTorch on TPU: Hands On With Colab

    Demonstrates running PyTorch models on TPUs via Colab for faster training. · for ML engineers, research engineers

    devtoSteadyai2d ago
  9. 9
    18

    PyTorch: a reference language

    Reference language · for ai researchers

    lobstersCooling 2 · pytorchai90d ago
  10. 10
    16

    OpenArch – PyTorch implementations of modern LLM architectures

    OpenArch offers PyTorch implementations of recent LLM designs for rapid experimentation. · for ml engineers

    hackernewsSteadyai42d ago
  11. 11
    16

    Google open-sources TorchTPU, a native PyTorch back end for TPUs

    Google open-sources TorchTPU, enabling native PyTorch execution on TPUs for faster model training. · for ml engineers, platform teams

    hackernewsSteadyai5d ago
  12. 12
    15

    Decoder-only Transformer has decreasing validation loss but generates repetitive or incoherent text

    Shows decoder-only transformer loss drops while output becomes repetitive, indicating training issues. · for ml researchers

    stackoverflowSteadyai63d ago
  13. 13
    13

    Accelerating Generative AI with PyTorch II: GPT, Fast

    Generative AI accelerated · for ai researchers

    lobstersSteady 4 · gptai80d ago
  14. 14
    10

    Your quantized model got worse, and nothing told you

    Model performance decreased · for ml engineers

    devtoSteady 2 · flutterai83d ago
  15. 15
    8

    GPU-Accelerating MSCRED with CUDA, im2col, GEMM, and a Custom PyTorch Extension

    Faster msc red with cuda · for pytorch devs

    devtoSteadydevtools81d ago
  16. 16
    7

    google/timesfm-3.0-pytorch (time-series-forecasting)

    Google released TimesFM 3.0 PyTorch model for time-series forecasting with safetensors. · for data scientists

    huggingfaceSteady 2 · pytorchdata−18 saturated55d ago
  17. 17
    7

    Bringing PyTorch Monarch to AMD GPUs

    PyTorch on AMD GPUs · for ai devs

    hackernewsSteadyai92d ago
  18. 18
    6

    openai/whisper-large-v3 (automatic-speech-recognition)

    New speech recognition · for ai devs

    huggingfaceSteady 3 · openaiai−23 saturated76d ago
  19. 19
    4

    PyTorch/Captum: RuntimeError: gather(): Expected dtype int32/int64 for index

    Fix PyTorch runtime error · for ai engineers

    stackoverflowSteadyai97d ago
  20. 20
    4

    How to create a custom dataset and dataloader in pytorch geometric for files with different dimensions?

    Create custom dataset · for ai researchers

    stackoverflowSteadyai101d ago