Claude 3.5 Sonnet & Artifacts are excellent resources for studying! SmythOS's sophisticated features can further improve your educational experience. #SmythOS #AIResearch #
@AliAliasКүн бұрын
Thanks good tutorial, Share code ❤
@automatalearninglabКүн бұрын
@@AliAlias already did! Check below!
@albertoprospero4330Күн бұрын
Great video! I also follow you on O'Reilly, and your lectures are really very insightful. It seems to me that you put a lot of passion and determination into what you do. Keep it up! Also, I would like to ask you one question: is it possible to provide also structured Pydantic input to openai function calling? In other words, in your code is it possible to transform "tool_create_directory" into a Pydantic class? I did not find very much documentation on that.
@automatalearninglabКүн бұрын
@@albertoprospero4330 in function calling you get structures inputs by default. Thanks! :)
@LearningWorldChatGPT3 күн бұрын
Your video is fantastic ! A quick question: I use Function Calling a lot. But is this new release from OpenAI, "Structured Outputs", better than using Function Calling? Does using one or the other affect Scalability in any way? Or does it make sense to use either? Thank you very much !
@automatalearninglab3 күн бұрын
@@LearningWorldChatGPT structures output is about getting an output in a Joan like structure. Function calling is about calling functions with LLMs to perform actions like web search and so on, it’s not about one or the other, it’s about what is your specific use case :)
@DhruvPatel-i5j7 күн бұрын
great Video
@automatalearninglab7 күн бұрын
Thanks!! :)
@marcbaumholz73289 күн бұрын
can you link the Blogpost you got this from here in the comments please ?
@automatalearninglab9 күн бұрын
You mean this one? langchain-ai.github.io/langgraph/#step-by-step-breakdown
@MarceloSilva-zt2ux10 күн бұрын
Great channel. How do you place these circles around the mouse pointer?
@automatalearninglab10 күн бұрын
its an app I bought costs like 7 bucks, its really nice! Called cursorPro :)
@marcanttins14 күн бұрын
Amazing
@automatalearninglab14 күн бұрын
thank youuu
@marcanttins14 күн бұрын
Amazing
@automatalearninglab14 күн бұрын
thankssss hehe
@marcanttins14 күн бұрын
Amazing
@S-Lingo16 күн бұрын
2:56
@bigdlamz18 күн бұрын
Excellent presentation, very simple & clear articulation for a highly complex topic
@automatalearninglab18 күн бұрын
@@bigdlamz thanks!!! 😊
@TooyAshy-10019 күн бұрын
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?
@automatalearninglab19 күн бұрын
Havent' used LangTrace. LangSmith is an evaluation and monitoring platform created on top of langchain so you can inspect everything that happens between chains which are these building blocks of processing that happens within these agentic workflows. LangGraph allows you to create workflows that mix determinic processing of inputs and outputs along with LLM processing (less deterministic). AutoGen takes a multi-agent approach that leverages some communication principles and concepts like 'conversation programming' to allow for implementing complex agentic workflows to solve complex tasks, is a different approach than this gtraph based approach that langgraph takes. Llama index was previously a rag focused platform but now they are also steering towards agentic workflows as the field sees its the best approach to actually tackle complex problems. Platforms like LangSmith are going to be key because anyone working with these systems sees that the issue always goes back to evaluation practices, monitoring etc....that's it! Cheeers! :) (thanks for watching!)
@bluetensee22 күн бұрын
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?
@automatalearninglab22 күн бұрын
If you want something already like structured as an actual app, try out gpt-engineer. IT will spit out the code already in a github repo. However, if you're working with Claude 3.5 sonnet and artifacts you can download the code generated, then ask it to create the folder structure with steps to execute the created app. It will spit out all the steps needed plus the packages to install etc....from there its like super easy to set upyour working app locally! Hope that helps! :) cheers!
@bluetensee22 күн бұрын
@@automatalearninglab thank's a lot!:). i'm a total beginner when it comes to these kinda things. can't even code. but maybe one day you'll make a beginners guide called "from sonnet -to- finished local app":) cheers, Mat (from Germany)
@automatalearninglab22 күн бұрын
@@bluetensee haha that's a cool idea!
@beatrizbelbut486223 күн бұрын
Eu pessoalmente gosto de ambos o Claude e o ChatGPT, mas nada bate um Lucas Soares 😍😍😍
@automatalearninglab23 күн бұрын
hahahah thank you! ;)
@AlexandreAugustin23 күн бұрын
If you would have budget to only have one paid AI. Would you invest in Claude our ChatGPT?
@automatalearninglab23 күн бұрын
I think as a developer I would choose Claude, as a non developer I would go with ChatGPT. :)
@rabibalam561025 күн бұрын
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...
@automatalearninglab25 күн бұрын
i do have it, and I have Artifacts feature enabled. Check it under settings if you also have that enabled.
@IdPreferNot127 күн бұрын
Nice video. Like that you walk through in real time... including showing how much co-pilot currently sucks.
@automatalearninglab27 күн бұрын
@@IdPreferNot1 hahaha yeah that was not planned but I’m sure they’ll update it
@AlexandreAugustin27 күн бұрын
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!
@automatalearninglab27 күн бұрын
@@AlexandreAugustin for small scale tasks use the 8B, and for efficient tool calling 70b. Is really good. I am using both in this video
@DrBeeWay28 күн бұрын
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.
@automatalearninglab28 күн бұрын
Oh. nice! Great idea! :)
@akulchopraАй бұрын
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?
@automatalearninglab29 күн бұрын
That's awesome! Hit me up on LinkedIn! :) www.linkedin.com/in/lucas-soares-969044167/
@akulchopra28 күн бұрын
Sure thanks@@automatalearninglab
@v-for-victoryАй бұрын
🎯 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 KZbin statistics from a downloaded CSV, - Discusses issues with visualization layout and potential improvements.
@automatalearninglabАй бұрын
@@v-for-victory nice
@yasminesmida2585Ай бұрын
which SLM you would recommend for handling summaries in both English and French .thank you
@automatalearninglab26 күн бұрын
Not aware of good ones for French but I would fine tune llama3.1 70b or 8B probably
@virtualbloxx181Ай бұрын
its free?
@siddharthduggalАй бұрын
hey, I'd like to sponsor you for my ai software - let me know how I can contact you to chat further
@carlosperezcpeАй бұрын
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
@automatalearninglabАй бұрын
@@carlosperezcpe Nice! Thanks! :)
@marcanttinsАй бұрын
Amazing
@automatalearninglabАй бұрын
@@marcanttins tx!
@marcanttinsАй бұрын
Amazing
@marcanttinsАй бұрын
Amazing
@marcanttinsАй бұрын
Amazing
@marcanttinsАй бұрын
Amazing
@automatalearninglabАй бұрын
@@marcanttins tx !
@marcanttinsАй бұрын
Amazing
@automatalearninglabАй бұрын
@@marcanttins tx! :)
@marcanttinsАй бұрын
Amazing
@automatalearninglabАй бұрын
@@marcanttins tx!
@khanhnguyenxuan4042Ай бұрын
Some features my not work on the preview section. You have to add the code to the real application and run it
@automatalearninglabАй бұрын
@@khanhnguyenxuan4042 yeah sure. I think here I was just trying to explore possibilities around the topic of learning etc
@user-ij6lq6kd9dАй бұрын
Thanks for the introduction for the application of ChatGPT with Anki!
@automatalearninglabАй бұрын
Thank youuuu
@guilhermenicolosi7817Ай бұрын
Great stuff
@cameosisj6007Ай бұрын
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!
@automatalearninglabАй бұрын
@@cameosisj6007 oh I’m glad! Thanks for watching!
@TooyAshy-100Ай бұрын
Thank you for sharing your knowledge; it was highly informative. 👍
@automatalearninglabАй бұрын
You're welcome!
@lucidmortoАй бұрын
Nice video!
@automatalearninglabАй бұрын
Thanks! :)
@koen.mortier_fitchenАй бұрын
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
@automatalearninglabАй бұрын
Yep, the whole experience with artifacts plus great code generation plus this atomic control over the code snippets make this a great tool! I have some other ideas lined up for what to build with it! :) Thanks for watching!
@carlosbaraldi124Ай бұрын
Amazing
@automatalearninglabАй бұрын
@@carlosbaraldi124 thanks!
@amuthanrithish7085Ай бұрын
how do i create virtual environment in linux could you please tell how cause i have to do this project
@automatalearninglabАй бұрын
easy, just download anaconda or miniconda, then run the cmd to create the environment like: conda create -n env-name python=<python version> then activate the env with 'conda activate env-name' and now you can install packages with pip install <package> Hope this helps! :)
@tdluluАй бұрын
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.
@automatalearninglabАй бұрын
THat's the artifacts feature that you have to enable! :)
@Mr_Kweeba18 күн бұрын
This drove me crazy too!!! Basically, in Claude you click on your name at the bottom left of the main window. Then click on "Feature Preview". When the window pops up, you will see the Artifacts artical/preview appear and in the last third of that window, you will see an "Artifacts" slider switch that you can turn on and off. That's it! I found it by sitting through a bunch of videos and in one video it was quicky mentioned so I got lucky, but really it could be mentioned a lot more, especially when these video makers are referencing the Artifacts feature!
@automatalearninglab18 күн бұрын
@@Mr_Kweeba agreed! 😎
@ameliuskiki4009Ай бұрын
What is your plan on claude ai ? I see you have unlimited messages to use
@automatalearninglabАй бұрын
I use the pro version!
@vinitkulal5207Ай бұрын
Can it give summarization for any research documents?
@duhai1836Ай бұрын
Love how other people use LLM's creatively. The code/flowchart example was amazing! Thanks Lucas!
@automatalearninglabАй бұрын
Thank you @duhai1836!
@er.shivam6919Ай бұрын
@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
@TooyAshy-100Ай бұрын
Thank you,,,
@automatalearninglabАй бұрын
Your welcome :)
@beatrizbelbut4862Ай бұрын
AAAAH coisa mais linda que eu já vi na minha vida (o youtuber) 😍😍😍 (mas o modelo é fixe também)
@automatalearninglabАй бұрын
🤣🤣🤣🤣rapariga tu não disfarça 🤣🤣🤣☺️
@beatrizbelbut4862Ай бұрын
@@automatalearninglab sua belezura que não disfarça 😘😘😘
@automatalearninglabАй бұрын
@@beatrizbelbut4862 hahaha
@HazemAzimАй бұрын
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
@automatalearninglabАй бұрын
I think function calling is definitely here to stay but I understand what you're saying about the hateful abstractions, I teach courses on these frameworks for OReilly Media and even for me is a pain to keep up with the complexiity and ever changing nature of these chaining abstractions.