Articles for category: AI Tools

Announcing Public Preview of AI/BI Genie Conversation APIs

As part of our Week of AI agents initiative, we’re introducing new capabilities to help enterprises build and govern high-quality AI agents. To that end, we are excited to announce the Public Preview of the Genie Conversation APIs, available on AWS, Azure, and GCP. With this API suite, your users can now leverage AI/BI Genie to self-serve data insights using natural language from any surface, including Databricks Apps, Slack, Teams, Sharepoint, custom-built applications and more. Additionally, the Conversation APIs enable you to embed AI/BI Genie in any AI agent, with or without Agent Framework. Using the Genie Conversation API suite,

FLUX1.1 [pro] is here – Replicate blog

If you’re paying attention to text-to-image AI leaderboards, you may recently have noticed a mysterious model named “blueberry” topping the charts. Well, today the cat’s out of the bag: blueberry is the codename for a new series of Flux models from our friends at Black Forest Labs. These new models are more powerful than any other open-source image generation models out there, and they are available to run on Replicate today: 🫐 replicate.com/black-forest-labs/flux-1.1-pro 🫐 replicate.com/black-forest-labs/flux-pro FLUX1.1 [pro] is a new model FLUX1.1 [pro] is a new, faster, more powerful version of FLUX.1 [pro]. It generates images six times faster than

Enhancing NLP Models for Robustness Against Adversarial Attacks: Techniques and Applications

The sphere of Natural language processing or NLP has undergone inspiring breakthrough due to the incorporation of state-of-art deep learning techniques. These algorithms have improved the internal flexibility of NLP models exponentially beyond human possibility. They have excelled in tasks such as text classification, natural language inference, sentiment analysis, and machine translation. By leveraging large amounts of data – these deep learning frameworks are revolutionizing how we process and understand language. They are inspiring high-performance outcomes across countless NLP tasks. Despite the advances that have been witnessed in the sector of Natural Language Processing (NLP) there are still open issues

Is LangGraph Used In Production?

Leading companies like Uber, LinkedIn, and Replit are choosing LangGraph to build agents that are not only powerful but also reliable. In 2024, the focus shifted towards specialized AI agents designed for specific business needs. But getting AI agents production-ready isn’t as simple as plugging in an LLM to produce intelligent outputs. Companies need solutions that provide reliability, observability, and control.  This piece explores the key challenges of putting AI agents into production and how leading companies like Uber, LinkedIn, and Replit are overcoming them, with some help from LangGraph. 🪄 Many companies are choosing LangGraph for reliable agents Companies

OpenAI Launches a Document and Code Editor Integrated Into ChatGPT

Was this newsletter forwarded to you? Sign up to get it in your inbox. Yesterday OpenAI gave a few writers, including Evan Armstrong and me, a private demo of a new ChatGPT feature from OpenAI called Canvas. It’s available today for all ChatGPT paid subscribers.  Canvas is a document and code editor that pops up natively inside of ChatGPT. Here’s a bit more about it, with some analysis from us. What Canvas is Canvas is OpenAI’s response to Claude Artifacts. There’s one big difference between Artifacts and Canvas: In Canvas, the document in the sidebar is fully editable by you,

Styling an HTML dialog modal to take the full height of the viewport

TIL: Styling an HTML dialog modal to take the full height of the viewport. I spent some time today trying to figure out how to have a modal element present as a full height side panel that animates in from the side. The full height bit was hard, until Natalie helped me figure out that browsers apply a default max-height: calc(100% - 6px - 2em); rule which needs to be over-ridden. Also included: some spelunking through the HTML spec to figure out where that calc() expression was first introduced. The answer was November 2020. Posted 14th March 2025 at 11:13

Release notes for Deephaven version 0.34

The wait is over, and Deephaven Community Core version 0.34.0 is out. This is a big release with significant enhancements and new features. Are you ready to explore the latest updates? Let’s dive in and discover what’s new! Command line interface for pip-installed Deephaven​ Do you run Deephaven from Python without Docker? If so, chances are it’s because: You don’t like Docker. You want to keep everything in Python. You like the Jupyter experience. Well, we have good news. It just got even easier to start Deephaven from Python with the introduction of a new command line interface. If you

Data Machina #251 – Data Machina

Six Nerdy AI Activities for the Long W/E. I’ve just read that lots of AI engineers in the US are running the rate race, feeling burnout. Here in the European AI scene things are innately a bit more relaxed. Aah… A long bank holiday in London; so much stuff to do in this amazing city! But if you are feeling the AI FOMO kick and can’t survive a long weekend IRL, here are six AI activities for you: Generate comics with AI. I gave it a go, generated a few short comics, and having fun so far. The AI team

From Prototype Purgatory to Production-Grade AI Agents

Subscribe • Previous Issues Taming the Wild West of AI Agents: Addressing the Challenges of Real-World Deployment AI agents are autonomous systems that combine language (and multimodal) understanding with the decision-making prowess of foundation models to interpret complex inputs, reason through multifaceted scenarios, and execute tasks autonomously. The business landscape is abuzz with excitement, as industry analysts forecast billions of dollars in value creation and early adopters report significant improvements in operational efficiency, customer engagement, and data-driven decision-making. With substantial market investments driving this momentum, the critical question for application builders is not whether to deploy AI agents, but how to seamlessly