Articles for category: AI Tools

March 9, 2025

ikayaniaamirshahzad@gmail.com

Mixture of Experts LLMs: Key Concepts Explained

Mixture of Experts (MoE) is a type of neural network architecture that employs sub-networks (experts) to process specific input parts. Only a subset of experts is activated per input, enabling models to scale efficiently. MoE models can leverage expert parallelism by distributing experts across multiple devices, enabling large-scale deployments while maintaining efficient inference. MoE uses gating and load balancing mechanisms to dynamically route inputs to the most relevant experts, ensuring targeted and evenly distributed computation. Parallelizing the expert, along with the data, is key to having an optimized training pipeline. MoEs have faster training and better or comparable performance than

March 9, 2025

ikayaniaamirshahzad@gmail.com

Delivering Generative Marketing Content to Customers

Marketers have long dreamed of one-on-one customer engagement, but crafting the volume of messages required for personalized engagement at that level has been a major challenge. While many organizations aim for more personalized marketing, they often target large groups of thousands or millions of customers within which a large amount of diversity still exists. Although this is better than a generic, one-size-fits-all approach, organizations would prefer to be more precise, if only they had the bandwidth to engage at a more granular level. As mentioned in our previous blog, generative AI can help ease the challenge of creating highly tailored

March 9, 2025

ikayaniaamirshahzad@gmail.com

Wan2.1 parameter sweep – Replicate blog

We’ve been playing with Alibaba’s WAN2.1 text-to-video model lately. Like most image and video generation models, Wan has a lot of input parameters, and each of them can have a profound impact on the quality of the generated output. What happens when you tweak those mysterious inputs? Let’s find out. The experiment We wanted to see how the guidance scale and shift input parameters affect the output. For our experiment, we used the the WAN2.1 14b text-to-video model with 720p resolution. To do this, we did what’s called a “parameter sweep”, systematically testing different combinations of input values to understand

March 9, 2025

ikayaniaamirshahzad@gmail.com

Exploring the TextAttack Framework: Components, Features, and Practical Applications

Over the last few years, a growing interest has been in testing the adversarial robustness of natural language processing (NLP) models. The research in this area covers new techniques for generating adversarial examples and defending against them. Comparing these attacks directly is challenging because they are evaluated on different data and victim models. Replicating earlier work as a baseline takes time and increases the risk of errors because of missing source code. Perfectly replicating results is also challenging because of the tiny details left out of the publications. These issues create challenges for benchmark comparisons in this space. Frameworks like

March 9, 2025

ikayaniaamirshahzad@gmail.com

Flash in the Pan or Future Standard?

Model Context Protocol (MCP) is creating quite the stir on Twitter – but is it actually useful, or just noise? In this back and forth, Harrison Chase (LangChain CEO) and Nuno Campos (LangGraph Lead) debate whether MCP lives up to the hype. Harrison: I’ll take the position that MCP is actually useful. I was skeptical on it at first, but I’ve begun to see its value. Essentially: MCP is useful when you want to bring tools to an agent you don’t control. Let me give an example. For Claude Desktop, Cursor, Windsurf – as a user, I don’t control the

March 8, 2025

ikayaniaamirshahzad@gmail.com

What Can Language Models Actually Do?

The world has changed considerably since our last ”think week” five months ago—and so has Every. We’ve added new business units, launched new products, and brought on new teammates. So we’ve been taking this week to come up with new ideas and products that can help us improve how we do our work and, more importantly, your experience as a member of our community. In the meantime, we’re re-upping four pieces by Dan Shipper that cover basic, powerful questions about AI. (Dan hasn’t been publishing at his regular cadence because he’s working on a longer piece. Look out for that

March 8, 2025

ikayaniaamirshahzad@gmail.com

OpenAI Stargate Joint Venture Demystified

The Open AI Stargate Joint Venture announcement had many folks heads turning, despite us calling out the capital requirements for OpenAI’s immediate plans months ago. The headline $500 billion is such an earth-shattering number that it also caused deserved skepticism from folks like Elon Musk stating that Softbank has well under $10 billion of funding secured. Sam Altman clapped back by saying it was already under construction, and to come visit it. Cluster Measuring Contest It’s fun to see the elite are going through their measuring contests with clusters but also they are both right to some extent. Softbank doesn’t

March 8, 2025

ikayaniaamirshahzad@gmail.com

Cutting-edge web scraping techniques at NICAR

Cutting-edge web scraping techniques at NICAR. Here’s the handout for a workshop I presented this morning at NICAR 2025 on web scraping, focusing on lesser know tips and tricks that became possible only with recent developments in LLMs. For workshops like this I like to work off an extremely detailed handout, so that people can move at their own pace or catch up later if they didn’t get everything done. The workshop consisted of four parts: Building a Git scraper – an automated scraper in GitHub Actions that records changes to a resource over time Using in-browser JavaScript and then

March 8, 2025

ikayaniaamirshahzad@gmail.com

Deephaven and Iceberg | Deephaven

Deephaven is a powerful analytics engine that makes processing large data more intuitive than ever. Iceberg is a table format that provides fast, efficient, and scalable data storage. Combining the two is like bringing Holmes and Watson together to solve a mystery. In this blog, we’ll explore Deephaven’s new Iceberg integration, why it matters, how to use it, and what’s to come. Deephaven already has integrations with SQL, Parquet, Kafka, and CSV, which can all be used as storage backend for a Deephaven-powered application. Now Iceberg is part of that list as well. If you’re looking for a scalable, efficient,