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2:56

Excellent presentation, very simple & clear articulation for a highly complex topic

Thank you! I love the videos from this channel. They're always so informative and helpful! Could you explain how LangGraph, AutoGen, Semantic Kernel, LlamaIndex and Haystack differ in their approach to creating agentic workflows? Specifically, how do these tools integrate with each other, and what are the unique advantages of using each tool individually or together in a project? Additionally, could you discuss the roles of LangSmith and LangTrace AI in this context and how they compare or complement the other tools?

hey. nice video idea! i don't understand how you then can create a working app ? do you have to take the created code and put it into android studio?

Eu pessoalmente gosto de ambos o Claude e o ChatGPT, mas nada bate um Lucas Soares 😍😍😍

If you would have budget to only have one paid AI. Would you invest in Claude our ChatGPT?

Do you have pro- subscription? I tried the exact prompt but it didn't render any app for me. Instead, gave me instructions on how to do it...

Nice video. Like that you walk through in real time... including showing how much co-pilot currently sucks.

What size of Llama3 are you using? At which point it starts not being useful? I really struggle to decide which size to use. Great video!

Great video with deep insights and high levels. It will be good to combine a second video with runnable codes to visually see the results.

Love this man... our projectlife foundation is rehumanising mother and child care through tech for the doctors, would love to discuss what we are doing with you and find a possible collaboration, i am sure you will love what we are working on. How can we connect?

🎯 Key points for quick navigation: 00:00 *🧩 CLA 3.5 and Artifacts Overview* - CLA 3.5 is a new model by Anthropic with superior performance metrics compared to GP4. - Artifacts enable standalone interactive content alongside CLA conversations, enhancing dynamic coding experiences. - Example: Building interactive quiz apps from PDF content using CLA 3.5 and Artifacts. 01:51 *📝 Interactive Quiz App Development* - Using CLA 3.5 and Artifacts to create quizzes based on PDF content. - Features include generating multi-choice and open-ended questions dynamically. - Example: Iterative improvement of quiz app interface and functionality. 07:47 *🗺️ Interactive Mind Maps* - Generating draggable mind maps to visualize large language model use cases. - Enhancing readability and usability of generated mind maps through iterative adjustments. - Example: Exploring different visualization layouts and customization options. 11:11 *🔄 Flowchart Generation from Code* - Using CLA 3.5 and Artifacts to create flowcharts from Python code snippets. - Iterative development to refine flowchart visualization and interactivity. - Example: Building a dynamic interface linking code segments to flowchart nodes. 19:43 *📊 Interactive Data Visualizations* - Exploring CLA 3.5 capabilities in generating interactive data visualizations. - Utilizing artifacts to create visual representations directly from structured data files. - Example: Demonstrating real-time customization and usability of interactive data displays. 23:34 *📊 Data Simulation and Code Generation* - Demonstrates generating simulated data and code within Cloud Sonnet, - Highlights creating a table with simulated plant growth and soil pH levels, - Initiates data organization into CSV format and visual dashboard creation. 25:07 *📈 Building Interactive Dashboard* - Shows how to build an interactive dashboard to visualize data dynamically, - Integrates simulated data into a dashboard with adjustable parameters, - Illustrates plotting growth rate against soil pH for different vegetables. 26:47 *📊 Uploading and Visualizing CSV Data* - Guides uploading CSV data and creating an interactive dashboard, - Demonstrates visualizing CZcams statistics from a downloaded CSV, - Discusses issues with visualization layout and potential improvements.

which SLM you would recommend for handling summaries in both English and French .thank you

its free?

hey, I'd like to sponsor you for my ai software - let me know how I can contact you to chat further

Love it, try to ask it for suggestions of design and usability. The results are so much beater than what you are geting. Hope it helps

Amazing

Amazing

Amazing

Amazing

Amazing

Amazing

Amazing

Some features my not work on the preview section. You have to add the code to the real application and run it

Thanks for the introduction for the application of ChatGPT with Anki!

Great stuff

Definitely hit my niche as a Claude 3.5 + Anki learner who wants to optimize my flashcards. Very informative and gives me a lot of ideas. Even just the idea of Claude's coding errors being more of a speed bump than a dead end. I finally have a reason to try Artifacts, thanks!

Thank you for sharing your knowledge; it was highly informative. 👍

Nice video!

Agreed. It’s a bit better than 4o bc it doesn’t split output code. And it can immediately show the code instead of copy-pasting to something like codepen to get a visual

Amazing

how do i create virtual environment in linux could you please tell how cause i have to do this project

at 2:38 how did the window on the right just appear for you? Are you using a specific version of Claude 3.5 Sonnet? I am using the free version of Claude.

What is your plan on claude ai ? I see you have unlimited messages to use

Can it give summarization for any research documents?

Love how other people use LLM's creatively. The code/flowchart example was amazing! Thanks Lucas!

@automatalearninglab I am facing an error in running this script help me out. I had done exactly what you told to do. File "C:\Users\User\Downloads\voice_analyzer_kyro\voice_analyzer.py", line 27, in <module> model = whisper.load_model("base") ^^^^^^^^^^^^^^^^^^^^^^^^^^ File "c:\Users\User\Downloads\voice_analyzer_kyro\.env\Lib\site-packages\whisper\__init__.py", line 154, in load_model model.set_alignment_heads(alignment_heads) File "c:\Users\User\Downloads\voice_analyzer_kyro\.env\Lib\site-packages\whisper\model.py", line 251, in set_alignment_heads mask = torch.from_numpy(array).reshape( ^^^^^^^^^^^^^^^^^^^^^^^ RuntimeError: Numpy is not available

Thank you,,,

AAAAH coisa mais linda que eu já vi na minha vida (o youtuber) 😍😍😍 (mas o modelo é fixe também)

I loved the first half of the video talking about agents from scratch , this is very educational and not highly covered . all stuff use llama Index, Langchain and other frameworks which is my opinion is a hateful abstraction . with gpt-4o I think we will not even the cumbersome OpenAI function calling

Awesome video,

If you could choose an actionable o’reilly course to learn & begin earning money as a freelancer, what would you choose? Any course which teaches real life implementation.

Can i get ur githhub repo link

Is it possible to also do speaker recognition? Do you have a video for it?

is the code available?

Amazing tutorial dude! Thanks 🙏

this video is a goldmine of knowledge, thank you

😍😍😍

Top !

Great video