New art project.
Train and inference GPT in 243 lines of pure, dependency-free Python. This is the *full* algorithmic content of what is needed. Everything else is just for efficiency. I cannot simplify this any further.
https://t.co/HmiRrQugnP
If you use Microsoft Authenticator to autofill your passwords on your phone, you will need to download Microsoft Edge and set it up as an autofill provider because they are removing the feature from Authenticator in July. https://t.co/DTk24t7fAr
Introducing Cerebras Inference
‣ Llama3.1-70B at 450 tokens/s – 20x faster than GPUs
‣ 60c per M tokens – a fifth the price of hyperscalers
‣ Full 16-bit precision for full model accuracy
‣ Generous rate limits for devs
Try now: https://t.co/39xaLQwNfj
Laws to ensure AI applications are safe, fair, and transparent are needed. But the White House's use of the Defense Production Act—typically reserved for war or national emergencies—distorts AI through the lens of security, for example with phrases like "companies developing any foundation model that poses a serious risk to national security."
Yes, AI -- like many technologies such as electricity and encryption -- is dual use in the sense it can be used for civilian or military purposes. But conflating AI safety for civilian use cases and military applications is a mistake.
It’s also a mistake to set reporting requirements based on a computation threshold for model training. This will stifle open source and innovation: (i) Today’s supercomputer is tomorrow’s pocket watch. So as AI progresses, more players -- including small companies without the compliance capabilities of big tech -- will run into this threshold. (ii) Over time, governments’ reporting requirements tend to become more burdensome. (Ask yourself: Has the tax code become more, or less, complicated over time?)
The right place to regulate AI is at the application layer. Requiring AI applications such as underwriting software, healthcare applications, self-driving, chat applications, etc. to meet stringent requirements, even pass audits, can ensure safety. But adding burdens to foundation model development unnecessarily slows down AI’s progress.
While the White House order isn’t currently stifling startups and open source, it seems to be a step in that direction. The devil will be in the details as its implementation gets fleshed out -- no doubt with assistance from lobbyists -- and I see a lot of risk of missteps. I welcome good regulation to promote responsible AI, and hope the White House can get there.
Need better network visibility on your @Azure Kubernetes Service (AKS) clusters? The Network Observability add-on is just for you! Read and learn more about this here
#AKS#AzNet#AzureNetworking
https://t.co/OAUyYYiqyw
We have now GA'ed our hosted Prometheus offering as part of Azure Monitor. It was announced at Build while I was on vacation. This is a fantastic offering - you don't have to run Prometheus, we do it for you.
https://t.co/V1zPDIUe7v
For more on reducing costs with Azure Monitor all up, have a look at this page.
Optimize costs in Azure Monitor - Azure Monitor | Microsoft Learn https://t.co/MPEb6K9dQW