Відео

Great talk and very crisp presentation. Big thanks!

Excellent Video and explanation

Very good

Are you the channel owner??

Do you have a video about beit or dino?

Very very very nice explanation!!! I like learning the foundation/origin of the concepts where models are derived..

😜 'promo sm'

Great explanation!

So it's a 50 mins Azure AI advert

Great Video!!

A lot of people take out their frusteration on AI systems and robots....the question is would that same person have hurt a living creature had that AI not existed?

Thank you. As someone navigating reported self-awareness by advanced LLMs I'd like to affirm the urgency of engaging with this topic.

Thank you so much, really useful!

Fantastic Video! Really loved the detailed explanation step-by-step.

I attended my first 'data science for good' meeting at ODSC West several years ago. It opened my eyes to algorithmic bias.

Im an avid admirer of Ben's native language in computer neural networks. Not so much with his Noosphere linguistics (⁠◔⁠‿⁠◔⁠)

I wish these issues would get more attention. AGI is the most important issue we face.

Ben always dropping knowledge bombs in the most random youtube channels lol

lots of improvement happening right now to llm but people have to go to efforts to fully unbox capabilities - using multi models, uncensored models, p2p data and model training, and especially real time data agg - once these barriers are overcome then we will see much better commercial use llm and it will happen even if it is a gradual process - the domain creep is real and the limitations and compromises will be diminished as we go brom big tech ai to really open source ai in the next 5 years - the hw/sw stacks have to mature and catch up as well but it is clear that this will happen - cxl and other accelerators will have massive impacts and once they do filter down from data centers to prosumers and home labbers and the small/med biz sector then we will see economies of scale kick in and much more innovation and development - not is not the time and although it may appear to be sort of a fever dream it probably will happen - more i/o like pci-e v6 is going to help, usb5 and faster networking will also help.

good contribution ... sir amzing video ....

thanks for the informative interview about how to interview!

Great interview, very useful information. I also love the online ai safety book, really great initiatives 👍

Thanks for sharing

when I run following code suggested in this video (at 8:19) for dynamic quantization it starts training with some random natural images for 100 epochs, I don't want to do training again I just wnat to quantize my pretrained weights: from ultralytics import YOLO import torch import torch.quantization model=YOLO('pre_trained_weights.pt') model.load_state_dict(torch.load('checkpoint.pth')) qmodel = torch.quantization.quantize_dynamic(model, dtype = torch.quint8)

thanks alot ))

How many RAI Parameter / Use cases this is tested against?

A - as always - very valuable conversation with Bostrom In my opinion, Sheamus McGovern is a terrible host. Two points. 1. He talks and chats for far too long instead of listening to his guest. A brief, directed outline of his question would benefit both the viewer and the guest. 2. His voice is terrible. He would have gained a lot if he could make himself audible through speech synthesis.

Excellent topic, very informative. Thank you!

This video provides a clear step by step explanation how to get from images to input features for Transformer encoders, which has proven hard to find anywhere else. Thank you.

Ms. Qi is altering the course of my life. Her honesty, integrity, kind consideration and upbringing inspire me. I've delved into everything about her. A financial loss of 1/3 of my retirement due to a banking error prompted me to cease trading in a fixed fund. Despite anticipating a quick correction, it took the bank two years to rectify, and they denied any responsibility. Frustrated, I missed out on the V-shaped rebound. Savvy investor friends cautioned against immediate action, and paid subscriptions taught me not to blindly trust them. I spent 10,000 hours focusing on fundamentals, employing geopolitical, macro, micro, banking, currencies, and NEWS analyses. While many lamented losses, I achieved a mid-double-digit gain this year alone. Enter Ms. Qi - my young hero. Unhindered by job offers due to her exceptional skills and honesty, Ms. Qi might have posed logical questions during her internship, facing resistance from supervisors who'd admired the wrong approach for decades. Her journey parallels Elon Musk's grandfather, who, beginning in a small Canadian town, became Canada's first licensed chiropractor and initiated the chiropractic association that still thrives. Confronting political issues led to his imprisonment and eventual relocation to South Africa. From my reading Ms. Qi's parents escaped a dark chapter in history as they left for America. Eventually, the figurehead of that traumatic event “hand picked” the seemingly least intelligent second-generation individual to protect those involved in the massacre. However, this "dumb" leader purged/incarcerated over a million of the original “cash cow” network, cleaning up a 40-year establishment and potentially jeopardizing the country’s future-a clear definition of “what goes around comes around”. Meanwhile, the two newcomers in America found solace in a simple life. Three decades later, Ms. Qi, once a little baby, now stands at the pinnacle of success, showcasing potential akin to Elon Musk's visionary genes. Inspired by her, I am revisiting day trading, recognizing the promise she holds for future generations.

thankyou much clearer

Maybe the most important question ever. Imagine the ethics/control/treatment of trillions upon trillions of sentient minds being dictated by the unethical 😳

MIT Math Dean

Solid high level overview of proven strategies.

thank you so much for sharing the talk it was really insightful. I'm a data scientist with three years of experience at an AI startup. I've worked in a small team and gained skills in data analytics, data engineering, data pipeline architecture, model training workflows, reproducibility, and process improvement. Now, I'm interested in leading new data projects and teams. Do the age and number of years of experience matter for such role?

What if in a document you are looking for multiple of the same fields? For instance, if there was a document with multiple different names, and you wanted to look for how many different names show up? I dont want individual fields for name 1 name 2 name 3, i just want them classified all as the same field "name".

Well explained!! ❤ THX a lot for sharing this.

sagoi my hero!

Thank you

Thanks for sharing. I'm keen to learn more about this.

If AI was actually intelligent it could destroy all of these programmer's jobs. Let me know when it can do that. Because I want it to do that.

Oops. I mis-poke about the history of data science. When I said mid-1990s... I meant to say mid-1900s! Thanks for having me on the show! I look forward to seeingyour next show coming up. ~ Adam

Great session 👏👏

awesome

Tax evader 🤮

🤮

Thank you, sir

great video