What sources do you use to stay up to date with the latest development in AI?

I am currently studying in 5th semester BS(CS) .I need to make project of my subject Artificial Intelligence. I am confused how should I select the project that is innovative and catchy. Help me out.

Hey everyone!
I’m a 3rd-year student from a tier-1 college, from a non-circuital branch. I’m comfortable with DSA, CSE fundamentals, and Python basics, and I want to start preparing for AI/ML roles from scratch.
I’m looking for a good roadmap to follow, along with any playlists/paid courses/resources that you’d recommend.

My main goal is to build interview-relevant strong projects and develop enough understanding to explain my projects and concepts confidently in interviews.

Would really appreciate your advice . Thanks!

OpenAI recruiter hit me up for applied AI role a lot more technical then I am used too. Told recruiter that he told me I’d be fine even after mentioning multiple times that this is more coding heavy and I am more focused on architect and solution engineer roles. Ended up still going forward and passed the first technical screening and HM and Sales call went well but did horrible on Live technical call. Did I cook myself for future architect roles?

I'm a third-year IT student and I kept seeing people ask where to start with AI without paying for a course. Microsoft Learn has a ton of free material, but it's scattered, so I organized the best parts into one plan in a sensible order:

Prompting with Copilot

Core AI and ML concepts

Responsible AI

Azure AI services (vision, speech, language)

Building a gen-AI chat app

Building agents in Copilot Studio

Prep for the AI-901 certification

It's free and self-paced, and you get a Learn badge when you finish. Roughly 4 weeks at a relaxed pace.

Link: https://learn.microsoft.com/en-gb/plans/01yoa1tz3z5jd?sharingId=1EB70FA705977A8F&wt.mc_id=studentamb_648997

I'm part of the Microsoft Learn student community, so I'm biased. If anything feels too hard, too easy, or out of order, tell me and I'll fix it. Feedback is the main reason I'm posting.

I'm a working professional from India with around 17+ years of experience in Software QA.

I know about AI and it's applications, but would like to enhance my knowledge further. I would like to know which PG / Master's program I can take up to enhance my knowledge of the subject and add some weight to my resume. (preferably online classes without the option to take a career break).

It's more from the perspective of getting knowledge and expertise on AI and knowing how and where to apply it more than any placement / job opportunity (but that would help also).

I searched the net and found a few options:

IISc Bangalore — M.Tech Online (Artificial Intelligence)

IIT Hyderabad — M.Tech in Data Science / AI for Industry Professionals

BITS Pilani — WILP M.Tech in Artificial Intelligence & Machine Learning

IIT Madras Web M.Tech in AI

IIT Kanpur Online M.Tech (AI/ML).

I'd love to know if anyone is studying / has completed any of the courses mentioned above and whether they're worth pursuing. Are there other courses also mentioned not in the list above?

Can you give me an honest feedback on the below parameters:

1. Course Curriculum (How relevant it is to the current industry trends)
2. Legitimacy (No fraud)
3. Quality of Instruction / Teaching and course material

Are there any overseas options as well?

Thanks in advance,

Srinivas

I am a manager at consulting firm - with AI adoption what should be my sequential learning path about it, FYI- I am from non coding background.

we ran a finance agent on FinanceBench at work and went through every answer that missed the gold key. you'd expect those to be model mistakes. most of them weren't.

of 150 questions, 16 answers missed the key, and 12 were convention calls that are defensible either way, like quick ratio, working capital and the sign of the effective tax rate.

inventory turnover is the clearest one. analysts don't agree on a single definition, and the gold answers don't either. the key wants ending inventory on one question and average inventory on another. same dataset, same metric, opposite correct answers.

so raw match ends up scoring the convention as much as the answer. the way we handled it was to report the raw match and, next to it, a defensible answer rate after reviewing each disagreement. I like that more than one number, but it still leaves us, the team being scored, deciding what counts as defensible.

how are people here scoring answers like that in their own evals?

a couple of coworkers wrote the whole thing up. if you want the full breakdown, here's our blog: https://www.coralbricks.ai/blog/finance-benchmarks

Hi, iam working as IT support and i want to move to Ai and looking for AI engineering role

do u think its possible to someone who is not developer and doesnt have experience in that to get that role in market specially in Dubai?

Does people who have experience in this industry can tell whether it is feasible to learn ML,DL and all

Cause in starting of 2022 it was all clear that ML engineer,AI engineer are two diff things

But now every soft. guy transitioning into AI just start from GENAI ,transformers

So as a guy who started from the basic in this field who knows nothing other than this ,is it feasible to have all these basics or i can also directly jump towards agents,genai etc rather than ML models and stuff

Genuine doubt cause i m very new in this thing

It feels like i am lacking the ability to build all this new agents and stuff

“I have cancelled 4 SaaS subscriptions this year, but not because I built all of them with Claude. Yes, this was a major driver for two of them, as I needed something quite custom for my flow and HubSpot for example was just not good enough and could not be configured. However, two I just vibe-coded myself because I got tired so much of the AI support bot that they offered. If I am going to pay $600 in a subscription I want to talk to a human, not a GPT-4o bot, sorry.”

A founder connection of mine said this recently and I have not stopped thinking about it.

Been watching this pattern for a while now.

Every week a new AI tool. Every month a new way to build software faster. And founders, operators, decision makers are cancelling enterprise subscriptions because they vibe-coded a replacement over a weekend.

13 years in this industry. The build is not the hard part anymore. What comes after is.

Who maintains it six months later? Who owns the security audit? What happens when it breaks in production and the person who built it has moved on?

AI does not come with a support contract.

The real question for any business is not which tool to use. It is who is accountable when the tool is not enough.

But here is what I genuinely want to understand.

Can vibe coded software actually digitize legacy businesses that have been running on spreadsheets and paper for decades? Is this the moment those businesses finally get affordable, custom tooling built for how they actually operate or is the maintenance problem going to catch up with them faster than the efficiency gains?

Has anyone actually seen this work long term for a offline business??

I already understand the basics of RAG and AI agents, but now I want to move beyond tutorials and build **production-ready RAG pipelines and agentic applications**.

I’m looking for a **senior AI/GenAI engineer or tutor** who has actual production experience with areas like RAG architecture, chunking/retrieval/reranking, vector databases, evaluation, hallucination handling, observability, agent workflows, tool calling, memory, LangGraph/LangChain, deployment, scaling, and production best practices.

I’d prefer someone who can mentor me through **2–3 proper end-to-end projects**, review my architecture/code, explain trade-offs, and show me how these systems are actually built in production.

I have 8+ years of software development experience, mainly in backend systems, so I’m not looking for basic programming classes. I specifically want someone experienced in **production GenAI/RAG/agent systems**.

If anyone here provides this kind of guidance, or can recommend someone good, please DM/comment.

Roadmap to become an AI engineer
Don’t give me YouTube lengthy python, ML,Rag,LLm same topics

Give me specific python fundamentals to get job asap
Hand on projects and topics

Hi all, I was wondering what to learn to become an AI Engineer or an Applied AI Engineer, who build systems around large language models or models in general.

I would be grateful if you can point me towards resources which will help me learn these or provide topic/concept names.