Bilal @muhambil

Joined September 2021

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Bilal @muhambil

2 years ago

@speedymachine1 @jeremyphoward I missed registering for the SolveIt course and wish I could still pay to join, but it seems registration is closed due to a full class. Do you know if the lectures will be made accessible to everyone later?

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Bilal @muhambil

2 years ago

@johnrobinsn @jeremyphoward @fastdotai Excellent work @johnrobinsn.

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Connor Leahy @NPCollapse

3 years ago

I had a great time addressing the House of Lords about extinction risk from AGI. They were attentive and discussed some parallels between where we are now and non-nuclear proliferation efforts during the Cold War. It certainly provided me with some food for thought, and some hope. AI is on an exponential, things are moving so, so incredibly fast. As we learned with COVID, there are only two times to react to an exponential - too early or too late. I think there should be a complete moratorium on development of AIs using unprecedented levels of computing power. Every time we do the next bigger AI run, we don’t know what’s going to pop out on the other side. Someday, it’s going to be Russian Roulette, and if you ever find yourself playing Russian Roulette, I have a recommendation: Stop. But the AGI companies are not stopping. And this is where the government comes in. When asked by the audience what exactly these recommendations to address risk from AI would look like, I recommended: 1. Liability for Developers and Users - strict liability for damage caused by AI systems that apply not just to the user, but also to the developer. If you develop a voice cloning system, and this is used by criminals to commit crimes, you should be liable too. 2. A Cap on Computing Power - companies cannot exceed a predetermined amount of ‘compute’ (computing power) when training their AIs. The more ‘compute’ used to power these AI systems, the more capable and dangerous they become. We recommend setting this cap on compute at 10^24 FLOP (around the size of ChatGPT). 3. A Global AI ‘Kill Switch’ - where governments build the infrastructure to be able to shut down powerful AI systems deployments and training runs if needed, and regularly test it with fire drills. We at Conjecture look forward to further engaging with UK legislators.

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Bilal @muhambil

3 years ago

@jeremyphoward Impressive. Thanks for sharing this. I’m working on Coronary Artery segmentation GC challenge with two people which are in high school. Surprised to see ideas they brought and implemented.

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Bilal @muhambil

3 years ago

@AndrewYNg @sama Congratulations. Well deserved.

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Bilal @muhambil

3 years ago

Delighted to share that I have been selected as a recipient of the prestigious Oracle for Research Fellowship Grant! 🎉 I am truly honoured and grateful to have been chosen for this opportunity. My deepest gratitude to Prof. Massimo Caputo and team, and my UWE colleagues.

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Bilal @muhambil

4 years ago

@MetaAI @ylecun Great. I read the MIM related sections. Awesome review of the state of the art. Well done. Thanks for sharing this.

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Bilal @muhambil

4 years ago

@DivGarg9 @OpenAI Incredible stuff. It will make our life so easy.

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John Robinson @johnrobinsn

4 years ago

▶️Object Detection from Scratch (Complete)👈I teach you how to build and train a multi-object detection model (YOLO/SSD) step-by-step storminthecastle.com/posts/05_ssd_f… Inspired by @jeremyphoward's 2018 @fastdotai course updated to use his latest #miniai library.

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Bilal @muhambil

4 years ago

Exciting 2-days in GREENGAGE kickoff and requirements workshop with a vibrant consortium of 17 industry, academic, and city partners from across the EU and UK. Lots of interesting ideas. It is a great opportunity to work with leading researchers and practitioners.

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Bilal @muhambil

4 years ago

@johnrobinsn @jeremyphoward Great work of creating multi label object detector from the scratch. Thanks.

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John Robinson @johnrobinsn

4 years ago

Part 3 🤩 Object Detection from Scratch. I teach you how to build and train a multi-object detection model (YOLO/SSD) step-by-step. storminthecastle.com/posts/03_compo… Following the same arc as @jeremyphoward's fantastic 2018 course covering the same topic but updated for FastAI v2!🔥

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Thomas Capelle @capetorch

4 years ago

🤩 Using diffusion models for next-frame prediction! Inspired by @jeremyphoward and friends' fastai course and the awesome miniai library, I put a simple pipeline to do next-frame predictions using DDPM 😎 wandb.me/mmnist

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Bilal @muhambil

4 years ago

@TheZachMueller @fastdotai Hi Zach, I purchased the course a couple of days ago but haven't seen any link for the live cohort. How can I participate?

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Bilal @muhambil

4 years ago

@johnrobinsn @jeremyphoward Excited to see it coming. Thanks.

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Bilal @muhambil

4 years ago

@suchisaria I‘be been working on a similar product Prescriberly which is designed for prescribers. We created a nice UI design for stakeholders engagement. The tool is to give top-k medication plans and check drug interactions across comorbidity, other drugs, and genetics. Happy to talk.

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Bilal @muhambil

4 years ago

@johnrobinsn @jeremyphoward Thanks, John for such a great tutorial. Fastai v2 version of OD was the long-awaited piece. Well-done.

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Radek Osmulski @radekosmulski

4 years ago

To learn Machine Learning fast you need to use the power of constraints. Here is what they are and how you can use them to learn 12x faster:

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Zach Mueller @ GTC Berlin @TheZachMueller

4 years ago

I've finally finished the content for Walk with @fastdotai! Which means the 25% off sale will end in TWO DAYS. Come learn from a world expert in the framework on how to use it efficiently, how to migrate from it, and other techniques to take you further! store.walkwithfastai.com/walk-with-fast…