AI Search Is Rewriting Discoverability. How Outset PR Adapts PR for LLM Visibility

Discover why some crypto outlets multiply PR placements through syndication while others don’t. OMI’s syndication data shows how reprints, aggregators, and outlet selection shape campaign visibility.

In this tutorial, we explore how to use Repowise to build repository-level intelligence for the itsdangerous Python project in a practical and reproducible way. We start with an already cloned repository, configure Repowise using the available LLM credentials, and initialize its indexing pipeline. We then inspect the generated .repowise artifacts, analyze the repository graph with […] The post How to Build Repository-Level Code Intelligence with Repowise Using Graph Analysis, Dead-Code Detection, Decisions, and AI Context appeared first on MarkTechPost.

ArXiv, a popular platform for preprint academic research, is taking a new step to attempt to reduce the volume of papers that include AI slop. If a paper has "incontrovertible evidence that the authors did not check the results of LLM generation," such as hallucinated references or "meta-comments" left by an LLM, authors will be banned from ArXiv for a year, according to Thomas Dietterich, ArXiv's section chair of its computer science section. Future ArXiv submissions will also have to be accepted at "a reputable peer-reviewed venue." Here's what he said on X: Attention @arxiv authors: Our Code of Conduct states that by signing your name … Read the full story at The Verge.

ICODA highlights growing importance of AI search visibility for crypto brands in 2026 digital markets. When a founder types “best DeFi protocols right now” into ChatGPT, Perplexity, or Gemini — their project either appears in the answer, or it doesn’t.…

Nous Research releases Token Superposition Training (TST), a two-phase pre-training method that cuts wall-clock training time by up to 2.5x at matched FLOPs by averaging contiguous token embeddings into bags during Phase 1 and reverting to standard next-token prediction in Phase 2 — without changing the model architecture, tokenizer, optimizer, or inference-time behavior. Validated at 270M, 600M, 3B dense, and 10B-A1B MoE scales. The post Nous Research Releases Token Superposition Training to Speed Up LLM Pre-Training by Up to 2.5x Across 270M to 10B Parameter Models appeared first on MarkTechPost.

I spent a weekend trying to convince a language model it was C-3PO. Here's what actually worked. The post What’s the Best Way to Brainwash an LLM? appeared first on Towards Data Science.

Alexa for Shopping is Amazon’s new AI-powered shopping assistant. | Image: Amazon Amazon is bringing Alexa Plus to Amazon.com, integrating its LLM-powered AI assistant directly into the company's shopping experience. Beginning today, when you type a query into Amazon, you'll be talking to Alexa for Shopping, the company's new shopping assistant, powered by Alexa Plus. So, while a search for "toilet paper" will still return the expected list of brands, typing "What's a good skincare routine for men" or "When did I last order AA batteries" will now trigger an answer from Alexa. Alexa for Shopping is replacing Amazon's Rufus AI shopping assistant and, unlike Rufus, it will be front and center in the Amazon app and on the … Read the full story at The Verge.

Explore what defines effective crypto PR in 2026. Learn how trust, AI visibility, founder positioning, data-driven outreach, and sustained credibility shape successful Web3 communications.