AI Industry Summary: Key Developments (December 25-27, 2025) The artificial intelligence sector has experienced extraordinary momentum through the final weekend of 2025, marked by transformative corporate partnerships, major acquisitions, and shifts in competitive dynamics that will define the industry throughout 2026. The following represents the most significant developments of the past 72 hours. Infrastructure Consolidation: Nvidia's Historic $20 Billion Groq Acquisition Nvidia completed an agreement to acquire assets from Groq, a nine-year-old AI chip startup, in what constitutes the chipmaker's largest deal to date at $20 billion in cash. The transaction was finalized with remarkable speed, occurring merely three months after Groq's Series C funding round in September, which valued the company at approximately $6.9 billion at a $750 million raise. This represents extraordinary value creation in an accelerated timeframe and signals Nvidia's aggressive consolidation strategy in the competitive AI hardware space.[1] The acquisition is structured strategically: Groq's founder and CEO Jonathan Ross, who previously led Google's tensor processing unit (TPU) development, will transition to Nvidia alongside key executives to integrate the acquired technology. However, Groq will maintain operational independence as a separate entity, with its emerging cloud business excluded from the transaction. Nvidia CEO Jensen Huang emphasized that the deal will enhance the company's low-latency inference capabilities, extending its competitive reach across a broader range of AI inference real-time workloads.[2][1] This acquisition reflects a critical imperative: the race for specialized AI accelerators beyond Nvidia's traditional GPU architecture. Groq has set revenue targets of $500 million for 2025 driven by demand for low-latency inference chips—the hardware responsible for running AI models in production environments at speed. By acquiring Groq's assets and talent, Nvidia eliminates a potential competitor while absorbing technology that could strengthen its dominance in the high-margin AI infrastructure market.[1]

Depending which report/source you look at, the current number of AI tools fits somewhere between 12,000 to 90,000+. This make it exceedingly difficult to learn them all. Or even to learn which are better than the other for any specific task. AI tools are far more than fancy Google searches, of course they do that as well but that is merely scratching the surface of what is possible.

In the rapidly growing space of AI everything, the prompt is king. It is the question/request you ask of an AI tool, in the hope you get an accurate answer. The more detailed and specific you get, often times the better the output I am in a build-a-thon style program at present with Lovable, it's an AI app builder. It's been a lot of fun and a massive learning curve. I have twice built something so far, only to realise I need market to buy it, not just making a cool tool. I know this but it has been a stark reminder because you can build and iterate so quickly and cheaply. These tools are not free, even though some have free access to begin with, it's a much better experience and output if you are on the paid version. I pay for Lovable and Grok at the moment. I have also been using Claude, Open AI, Co-Pilot and Gemini, Builder & DataButton Comment what systems you have tried

Currently I have the following AI tools in use regularly; - Grok - paid - Gemini - paid, as part of my Google Workplace subscription - NotebookLLM - paid, as part of my Google Workplace subscription - Perplexity - paid, including their Comet browser - Replit - paid Keep an eye out for more posts for expansion on the various platforms. I have also pinned this post and I will update and change it as I explore more tools.

Hi everyone! If you’re new to the Skool app, you can get notified when the others post in the group. So, if you want, you can go into the list of members and “follow” each one so you can start up to date with what’s going on in the group. Just an FYI.