Steven Wallace

[Steven Wallace @SteveWallace52]

Excited to share our work on automating crevasse detection on continental glaciers at the SAGES ASM at Heriot-Watt University last week.

#computervision #deeplearning #semanticsegmentation #glaciology #climatetech #SAGES #HeriotWatt

[Piotr Bojanowski @p_bojanowski]

I am happy to share the work of our team. The outcome of a collaborative effort, by a joyful group of skilled and determined scientists and engineers! Congrats to the team on this amazing milestone!

[Steven Wallace @SteveWallace52]

Thank you to the University of Aberdeen for inviting me to conduct a guest lecture during the Data Mining with Deep Learning module on the MSc AI yesterday. The lecture covered segmenting crevasses on continental glaciers in the Arctic Circle. #AI #segmentation

[Northern Lights Deep Learning Conference 2027 @nldlconference]

The proceedings for NLDL 2025 is now available at PMLR: https://t.co/9Ez8ay0w4z 🤖❄️

[Steven Wallace @SteveWallace52]

Thanks to NLDL 2025 for inviting me to present our work with SAM and SAM 2 published in Proceedings of Machine Learning Research. #nldl #ai #machinelearning #deeplearning

[Northern Lights Deep Learning Conference 2027 @nldlconference]

NLDL 2025 Day 1 Highlights: Exciting research showcases, discussions on diversity in AI, and Northern Lights! 🤖 🧠 🌍

A huge thanks to Day 1's invited keynote speakers, scientific presenters, and "Diversity in AI" speakers and panelists for a great first day here in Tromsø!

[Steven Wallace @SteveWallace52]

It was great yesterday to be given the chance to present our conference paper publication at the Nothern Lights Deep Learning Conference 2025 in Tromsø, Norway. #deeplearning #AI #nldl2025

[Steven Wallace @SteveWallace52]

It's time for the final poster presentation of 2024 at PhD Connect, Horizon Leeds. #AI #DeepLearning #MachineLearning #segmentation

[Steven Wallace @SteveWallace52]

There are some very interesting insights in this I have to say. #deeplearning #MachineLearning #LLMs #ai

[Andrej Karpathy @karpathy]

I gave a talk at GPU MODE workshop last week on llm.c

- the origin story of llm.c
- being naked in the world without PyTorch and having to re-invent Array, Autograd, Device, Dtype, Compile, Distributed
- how to port a PyTorch layer to 1) explicit PyTorch
- and then to 2) write the backward pass
- 3) port forward & backward pass to C
- 4) string all the layers together
- achieving one file of C with no dependencies that compiles and runs ~instantly, where all memory is pre-planned and allocated a single time, fully deterministic, portable code that can run on a potato or a von Neumann probe
- how most of llm.c was built at 1am-7am in a water villa porch in Maldives and why this is the recommended way to develop software
- convert all of it to run in CUDA on GPU in fp32
- port matmul to cuBLAS
- port attention to cuDNN flash-attention
- introduce bfloat16 mixed precision
- introduce many more optimizations and features like kernel fusions, Packed128, stochastic rounding, full determinism
- add multi-GPU training, NCCL, sharded optimizer
- add multi-node with MPI or file system or socket
- reproduce GPT-2 (1.6B) on one 8XH100 node in 24 hours for $672 in llm.c, achieving (at the time) 29% less memory, 19% faster training that PyTorch nightly, and much faster compile & run
- how open source development attracts Avengers from the internet
- port to training Llama 3 imminent (branch exists)
- many other notable forks
- last thought: how software abstractions like Python/PyTorch and everything else really exist only because humans are finite in knowledge, IQ and attention, and how with increasing AI capability LLMs may export custom binaries like llm.c for any application directly, tearing apart and refactoring all abstractions as needed.
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[Steven Wallace @SteveWallace52]

Thanks to the Interdisciplinary Research and Innovation Symposium 2024 for having me present a poster at the University of Aberdeen. Thanks to all the organisers for a well-run event. #DeepLearning #MachineLearning #ClimateCrisis

[Amir Atapour-Abarghouei @AmirAtapour]

It has been a very successful BMVA Computer Vision Summer School this year. Thanks to all volunteers and staff from @comp_sci_durham and my co-Chairs @TobyBreckon @UlrikBeierholm @jjdengjj @sttujames

[BMVA Summer School @BmvaCvss]

Dr Oscar Mendez @OscarMendezM delivered a talk on "Deep Learning for Computer Vision and Robotics" in the 27th BMVA Computer Vision Summer School in Durham University.

[BMVA Summer School @BmvaCvss]

Dr Gwangbin Bae @BaeGwangbin delivered on a talk on "Always-on Perception for 3D Computer Vision" in the 27th BMVA Computer Vision Summer School in Durham University.

[Steven Wallace @SteveWallace52]

I had a great experience at the BMVA Summer School 2024 at Durham University. Thanks to the organisers and all the speakers who participated in the event. #AI #deeplearning #MachineLearning #computersciencestudents #BMVC2024

[BMVA Summer School @BmvaCvss]

Prof. Victor Sanchez delivered a talk on "Contrastive Language-Image Pretraining (CLIP) for Video Analytics" in the 27th BMVA Computer Vision Summer School in Durham University.

[BMVA Summer School @BmvaCvss]

Dr Andrew Gilbert delivered a talk on "Video Understanding" in the 27th BMVA Summer School in Durham University.

[BMVA Summer School @BmvaCvss]

Dr. Paul Henderson @pmh47_ml delivered a talk on "Structured Generative Models for Computer Vision" in the 27th BMVA Summer School in Durham University.

[Steven Wallace @SteveWallace52]

It's been good to attend the BMVA 2024 Summer School. Great presentations and ideas were brought to the table this week. #AI #DeepLearning #MachineLearning #BMVA #BMVC

[BMVA Summer School @BmvaCvss]

Dr. Oya Celiktutan @oyaceliktutan delivered a talk on "Multimodal Behaviour Understanding and Generation for Human-Robot Interaction" in the 27th BMVA Computer Vision Summer School in Durham.

[BMVA Summer School @BmvaCvss]

A fantastic practical session led by Prof. Neill Campbell on "PyTorch for Computer Vision" in the 27th BMVA Computer Vision Summer School in the Department of Computer Science at Durham University.