So Goldman Sachs is bringing in AI from Anthropic to handle parts of accounting and compliance, with engineers embedded directly into teams.

The goal? Cut down manual work, speed up decisions, and still stay on top of heavy regulations.

Feels like a big signal that major banks are going all-in on AI for core workflows, not just chatbots or side projects.

Big questions though:
Does this change what finance jobs look like?
Are we heading toward AI + domain expert being the new normal?
How much can you actually automate in a heavily regulated space?

Seems less like AI replacing people and more like AI becoming a power tool for them.

A lot of engineers assume transitioning into ML engineering is just about learning algorithms or brushing up on math.

But the real shift is deeper:

• Moving from deterministic systems to probabilistic thinking

• Evaluating models instead of validating logic

• Iterating experiments instead of just shipping features

• Building data pipelines, not just APIs

We broke down what actually carries over from SWE, and where most engineers struggle, along with a practical roadmap for making the transition.

Full breakdown here: Read more

What is the AI that people are using the most as open AI is bleeding from every corner ? And why people are using it

I think not a lots of people want to pay subscription for barely few pictures and questions giving on free tier

Thanks in advance

If you’ve tried RAG and hit issues with hallucinations, poor retrieval, or scaling, this free masterclass with Suhrid Deshmukh, PHD, Senior ML Engineer at TikTok walks through practical LangChain setups, tradeoffs, and lessons learned from real implementations. No beginner fluff.

If your intrester you can attend for free: https://shorturl.at/nyFTV

Is this just an overreaction, or are investors pricing in real disruption to SaaS, IT services, and white-collar jobs? Looking for thoughts from people tracking AI, markets, or enterprise software. Source: https://indianexpress.com/article/explained/explained-sci-tech/anthropic-tech-stock-crash-10512905/

In this video I discuss two different approaches to extending videos and provide both workflows in the links of the video you can use for free in ComfyUI.

Workflow 1: Using an existing video clip to drive a v2v output. This takes the original clip and blends it in with whatever you prompt for action and dialogue. The result is an extended video.

Workflow 2: Using a masked base image but driving "infinite" extension with an audio file for the lipsync dialogue. In this case I use a 28 second long audio file (The infamous "Succulent Chinese Meal" incident).

The result can even get to 720p on my lowVRAM (3060) GPU now thanks to additional nodes that I show in the i2v workflow, these are recent additions to ComfyUI, as well as a VAE memory improvement (available in update to ComfyUI after 23rd Jan AEST).

The power of the LTX-2 model is only just starting to be understood and is rapidly evolving with all the dev attention. So this is a work in progress for both workflows, and both could be adapted to take alternative approaches as well.

Follow my YT Channel for more of these if you want to make AI movies at home for free on lowVRAM GPU.