Articles for category: AI Tools

March 14, 2025

ikayaniaamirshahzad@gmail.com

Bayesian Deep Learning is Needed in the Age of Large-Scale AI [Paper Reflection]

In his famous blog post Artificial Intelligence — The Revolution Hasn’t Happened Yet, Michael Jordan (the AI researcher, not the one you probably thought of first) tells a story about how he might have almost lost his unborn daughter due to a faulty AI prediction. He speculates that many children die needlessly each year in the same way. Abstracting away the specifics of his case, this is one example of an application in which an AI algorithm’s performance looked good on paper during its development but led to bad decisions once deployed. In our paper Bayesian Deep Learning is Needed

March 14, 2025

ikayaniaamirshahzad@gmail.com

Introducing Serverless Batch Inference | Databricks Blog

Generative AI is transforming how organizations interact with their data, and batch LLM processing has quickly become one of Databricks’ most popular use cases. Last year, we launched the first version of AI Functions to enable enterprises to apply LLMs to private data—without data movement or governance trade-offs. Since then, thousands of organizations have powered batch pipelines for classification, summarization, structured extraction, and agent-driven workflows. As generative AI workloads move into production, speed, scalability, and simplicity have become essential. That’s why, as part of our Week of Agents initiative, we’ve rolled out major updates to AI Functions, enabling them to

March 13, 2025

ikayaniaamirshahzad@gmail.com

Streaming spaCy

Join spaCy author and core developer Matt as he works on the library, develops features and fixes bugs, while chatting about all things NLP and open source. Every Thursday at 2pm CET and Friday at 11am CET. Source link

March 13, 2025

ikayaniaamirshahzad@gmail.com

We messed up: data URLs in our sync API

Earlier this month we announced a sync mode for our API, which makes it quicker and easier to get model output. On Oct 29, 2024, we made the difficult decision to roll back data URL responses as part of our sync API. This post explains why we’ve done this and what we’re going to do next. What happened? At the start of October, we began rolling out a sync mode for our API to make it easier for you to get model output quickly: When a client sends a Prefer: wait HTTP header to the API, we wait for up

March 13, 2025

ikayaniaamirshahzad@gmail.com

FLUX Image Generation with DigitalOcean

We have talked a lot about the capabilities and potential of Deep Learning Image Generation here on the Paperspace by DigitalOcean Blog. Not only are image generation tools fun and intuitive to use, but they are one of the most widely democratized and distributed AI models available to the public. Really, the only Deep Learning technology with a larger social footprint are Large Language Models. For the last two years, Stable Diffusion, the first publicly distributed and functional image synthesis model, has completely dominated the scene. We have written about competitors like PixArt Alpha/Sigma and done research into others like

March 13, 2025

ikayaniaamirshahzad@gmail.com

How Klarna’s AI assistant redefined customer support at scale for 85 million active users

Klarna has reshaped global commerce with its consumer-centric, AI-powered payment and shopping solutions. With over 85 million active users and 2.5 million daily transactions on its platform, Klarna is a fintech leader that simplifies shopping while empowering consumers with smarter, more flexible financial solutions. Klarna’s flagship AI Assistant is revolutionizing the shopping and payments experience. Built on LangGraph and powered by LangSmith, the AI Assistant handles tasks ranging from customer payments, to refunds, to other payment escalations. With 2.5 million conversations to date, the AI Assistant is more than just a chatbot; it’s a transformative agent that performs the work

March 13, 2025

ikayaniaamirshahzad@gmail.com

Is AI Progress Hitting a Wall?

Was this newsletter forwarded to you? Sign up to get it in your inbox. A wave of recent articles proclaims the death of deep learning. Leaked reports suggest OpenAI’s new model Orion finished training without showing nearly the improvement that GPT-4 achieved over GPT-3. Critics like Gary Marcus are already writing gloating eulogies. So, is AI progress slowing down? No. Let me tell you why. My nephew is 2 years old. Over the last year or so he’s rapidly become much more mobile. First, he learned to crawl, sticking his butt into the air and pushing with his knees to

March 13, 2025

ikayaniaamirshahzad@gmail.com

Training – CUDA Moat Still Alive – SemiAnalysis

Intro SemiAnalysis has been on a five-month long quest to settle the reality of MI300X. In theory, the MI300X should be at a huge advantage over Nvidia’s H100 and H200 in terms of specifications and Total Cost of Ownership (TCO). However, the reality is that the on paper specs as given below are not representative of performance that can be expected in a real-world environment. If AMD could deliver the below marketed performance with this memory, it would be a very strong competitor in the market.  Source: SemiAnalysis, Nvidia, AMD Today we are going to talk through our five-month journey

March 13, 2025

ikayaniaamirshahzad@gmail.com

Smoke test your Django admin site

Smoke test your Django admin site. Justin Duke demonstrates a neat pattern for running simple tests against your internal Django admin site: introspect every admin route via django.urls.get_resolver() and loop through them with @pytest.mark.parametrize to check they all return a 200 HTTP status code. This catches simple mistakes with the admin configuration that trigger exceptions that might otherwise go undetected. I rarely write automated tests against my own admin sites and often feel guilty about it. I wrote some notes on testing it with pytest-django fixtures a few years ago. Source link

March 13, 2025

ikayaniaamirshahzad@gmail.com

In response to Rockset-OpenAI: a brief real-time analytics manifesto

OpenAI’s acquisition of Rockset sent waves through the data infrastructure industry. On the heels of Databricks’ billion-dollar reach for Tabular, the industry is both in play and in flux. Companies like Clickhouse, StarTree, and Imply have published pieces that pontificate about the impact of OpenAI’s acquisition on the landscape and pitch their gear to Rockset customers looking for a Plan B. Even my loved ones aren’t interested in my armchair quarterbacking of OpenAI’s strategy, so I’ll let the All-In, Ben & Mark, and Acquired podcasts weigh in. However, as the CEO of Deephaven Data Labs, a company developing software for