What's next for AI agentic workflows ft. Andrew Ng of AI Fund

its so soothing to hear andrew ng's voice. brings me back to my coursera ML and DL courses

The AI legend, I can't forget how easy was learning complext deep learning stuff by just taking Andrew Ng's courses

Brilliant. The only thing I would add is that with inference speeds offered by Groq, it’s not necessary to wait minutes anymore. Fast inference speeds have the most value when humans aren’t reading the output.

It's nice to see Andrew finally be impressed by something! A lot of his previous talks were along the lines of how AI can't do anything yet and it's not nearly capable, etc.

Thank you Andrew Ng for certifying me 🙌

00:01:03 AI agents: Iterative, agentic workflows enhance performance. 00:04:29 Reflective agents: Self-assessment improves code quality iteratively. 00:09:22 Multi-agent collaboration: Diverse agents boost complex program generation. 00:12:01 Fast token generation: Rapid token output crucial for iterative workflows. 00:13:21 AGI journey: Agent workflows propel progress in AI development.

It is always a pleasure to hear Andrew!! :)

I use this method of agentic workflow for coding in school, with brainstorming, and detailed pseudo steps, then review it, then stich somethings together, and have it revise itself. Then after a few cycles, I give it a request using words like "magnificent," or "swe professional point of view," and other things along those lines. Which ends up give me a better product by the final iteration. I am a Sophomore CS student, and I'm glad I am doing the method right, when I'm practicing data structures. Thanks for explaining the method of what I have been doing Andrew Ng.

Mind-blowing... THANK YOU, Andrew! Great talk.

Clip #2 [4:26-6:16] I love how Dr Ng humbly describes his work as laying down another brick on the golden road to AGI.

Agree 100%. To reach AGI/ASI will require agentic workflows.

Andrew Ng as always great!

Hi guys, This is an excellent talk. I watched the Andrej one as well. And it seems that these talks are really focused and talk about real problems. So kudos to the team for executing on this. Its WAY WAY BETTER than these large conference interviews where you don't learn anything

Interesting talk on AI Agent, Andrew Ng. More updates on this subject will help. 🌞👏👏

Practical overview and feedback of what works and doesn't, very nice

Absolutely outstanding talk! Outstanding!

Great insights as always and I admire AndrewNG explain the advance tech explained in super simple manner !

Fascinating. I'll experiment with agentic workflows for my product. I really like the idea of getting more out of GPT3 using rag and these techniques.

I just did a quick test of this by customizing GPTs how I would like it to respond , its a good fame work , but i dont think its truly agentic . "Define the Goal: Be specific and measurable. What is the desired outcome of this workflow? Identify Key Milestones: Break down the overall goal into major checkpoints or phases. Flexible Action Steps: For each milestone, brainstorm a variety of potential actions that could move you forward. Avoid a rigid, sequential task list – these actions are options to choose from. Evaluation and Iteration: Determine how you'll measure progress towards milestones and the overall goal. Build in regular checkpoints for assessment. Be prepared to adapt actions, milestones, and even the goal itself based on results. Key Principles Outcome Focus: Prioritize reaching your goal over following a precise plan. Adaptability: Embrace change and be willing to pivot your actions as needed. Empowerment: This framework aims to give you agency and decision-making power within the process."

Love the analogy of the proverbial manager checking every 5 mins after assigning a task 🙃