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Prolego
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เข้าร่วมเมื่อ 6 เม.ย. 2020
We are an elite team of AI engineers and creative technologists committed to guiding the world’s largest companies through their AI transformation.
We do this by building custom, innovative solutions to solve complex business problems. We also help drive the cultural and process changes necessary to fully leverage AI.
We do this by building custom, innovative solutions to solve complex business problems. We also help drive the cultural and process changes necessary to fully leverage AI.
Ep 42. Your GenAI Project is Blind Without a Performance Evaluation Framework
Check out our GitHub repo 🔥 for more information about building a Performance Evaluation Framework for your LLM-based solution ➡️ hubs.ly/Q02Q7kyJ0.
Want to discuss 💬 your genAI project - get in touch with us at hello@prolego.com and be sure to sign-up for our newsletter here ➡️ hubs.ly/Q02NNJDT0
About Prolego
Founded in 2017, Prolego is an elite consulting team of AI engineers, strategists, and creative professionals guiding the world's largest companies through the AI transformation (www.prolego.com).
Want to discuss 💬 your genAI project - get in touch with us at hello@prolego.com and be sure to sign-up for our newsletter here ➡️ hubs.ly/Q02NNJDT0
About Prolego
Founded in 2017, Prolego is an elite consulting team of AI engineers, strategists, and creative professionals guiding the world's largest companies through the AI transformation (www.prolego.com).
มุมมอง: 126
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Ep 41. Your RAG Demo Is a Waste of Time
มุมมอง 85721 วันที่ผ่านมา
Interested in this topic 🔥 Join one of our free live workshops where talk in-depth about Performance-Driven Development. Register here ➡️ hubs.ly/Q02NNFdV0 You can read more about Performance-Driven Development on our Github page here ➡️ hubs.ly/Q02Q7kyJ0 Want to discuss 💬 your genAI project - get in touch with us at hello@prolego.com and be sure to sign-up for our newsletter here ➡️ hubs.ly/Q...
Ep 40. Skills and Team Design for LLM Applications
มุมมอง 17728 วันที่ผ่านมา
Interested in this topic 🔥 Join one of our free live workshops where talk in-depth about Performance-Driven Development. Register here ➡️ hubs.ly/Q02NNFdV0 🔥 Download Prolego's AI Systems Engineer Job Description template here ➡️ hubs.ly/Q02Q7jzK0 You can read more about Performance-Driven Development on our Github page here ➡️ hubs.ly/Q02Q7kyJ0 Want to discuss 💬 your genAI project - get in to...
Ep. 39 Best Practices for Scalable GenAI Solutions
มุมมอง 190หลายเดือนก่อน
Interested in this topic 🔥 Join one of our free live workshops where talk in-depth about Performance-Driven Development. Register here ➡️ hubs.ly/Q02NNFdV0 You can read more about Performance-Driven Development on our Github page here ➡️ hubs.ly/Q02NNFkt0 Want to discuss 💬 your genAI project - get in touch with us at hello@prolego.com and be sure to sign-up for our newsletter here ➡️ hubs.ly/Q...
Ep 38. Get Your GenAI Project On Track
มุมมอง 179หลายเดือนก่อน
Interested in this topic 🔥 Join one of our free live workshops where talk in-depth about Performance-Driven Development. Register here ➡️ hubs.ly/Q02NNFdV0 You can read more about Performance-Driven Development on our Github page here ➡️ hubs.ly/Q02NNFkt0 Want to discuss 💬 your genAI project - get in touch with us at hello@prolego.com and be sure to sign-up for our newsletter here ➡️ hubs.ly/Q...
How to Prepare for GPT-5
มุมมอง 4304 หลายเดือนก่อน
👨🏫 Free AI Abundance Workshop - multiple times available. Register here: lu.ma/prolego 📺 Ep 16. Case Study: Vericant Releases GenAI Solution in 30 Days: th-cam.com/video/Sz_F8p2fBBk/w-d-xo.html 📄 PROLEGO NEWSLETTER - Accelerate your generative AI journey with insights from people who know what they’re doing, sign up for the Prolego GenAI Newsletter: hubs.ly/Q02t4V640 🄿 ABOUT PROLEGO - Prolego ...
I failed. Time for a new approach.
มุมมอง 3715 หลายเดือนก่อน
AI Abundance Workshop - multiple times available. Register here: lu.ma/prolego
Ep 37. Call Your AI Project a Copilot
มุมมอง 4265 หลายเดือนก่อน
⬇️ ⬇️ FREE AI DOWNLOADS FOR SENIOR BUSINESS LEADERS ⬇️ ⬇️ PROLEGO LLM RAG Study. We recently released a playbook to help teams optimize LLM application performance. We expanded our efforts with a study assessing various optimization impacts. You can read the full study here: hubs.ly/Q02t4SXX0 or watch our online workshop with Pinecone here: hubs.ly/Q02t4Twb0. 📕 PROLEGO LLM OPTIMIZATION PLAYBOO...
Ep 36. Get a Quick Win with GenAI in 5 Weeks
มุมมอง 3896 หลายเดือนก่อน
PROLEGO OPEN SOURCE LLMs HAVE HIGHER ROI FOR ENTERPRISE GENAI. We recently released a playbook to help teams optimize LLM application performance. We expanded our efforts with a study assessing various optimization impacts. You can read the full study here: hubs.ly/Q02srDZ70. 📕 PROLEGO LLM OPTIMIZATION PLAYBOOK - download Prolego's free LLM Optimization Playbook and learn how to improve model ...
Ep 35. Don’t Fine-Tune Your LLMs
มุมมอง 8746 หลายเดือนก่อน
PROLEGO OPEN SOURCE LLMs HAVE HIGHER ROI FOR ENTERPRISE GENAI. We recently released a playbook to help teams optimize LLM application performance. We expanded our efforts with a study assessing various optimization impacts. You can read the full study at prolego.com/ragstudy. 📕 PROLEGO LLM OPTIMIZATION PLAYBOOK - download Prolego's free LLM Optimization Playbook and learn how to improve model ...
Ep 34. Supercharge Legacy ML Models with LLMs
มุมมอง 1946 หลายเดือนก่อน
PROLEGO OPEN SOURCE LLMs HAVE HIGHER ROI FOR ENTERPRISE GENAI. We recently released a playbook to help teams optimize LLM application performance. We expanded our efforts with a study assessing various optimization impacts. You can read the full study at prolego.com/ragstudy. 📕 PROLEGO LLM OPTIMIZATION PLAYBOOK - download Prolego's free LLM Optimization Playbook and learn how to improve model ...
Ep 33. Open-Source LLMs Are Enterprise Ready (FREE REPORT)
มุมมอง 3186 หลายเดือนก่อน
Ep 33. Open-Source LLMs Are Enterprise Ready (FREE REPORT)
Ep 32. Create a Thriving Creative Career in the AI Era
มุมมอง 3247 หลายเดือนก่อน
Ep 32. Create a Thriving Creative Career in the AI Era
Ep 31. Crush Your Presentation with AI-Generated Slides
มุมมอง 1.5K7 หลายเดือนก่อน
Ep 31. Crush Your Presentation with AI-Generated Slides
Ep 29. Prolego's LLM Optimization Playbook
มุมมอง 2.3K7 หลายเดือนก่อน
Ep 29. Prolego's LLM Optimization Playbook
Ep 28. How to Host Open-Source LLM Models
มุมมอง 3.1K8 หลายเดือนก่อน
Ep 28. How to Host Open-Source LLM Models
Ep 27. ServiceNow Reports Record Earnings from GenAI
มุมมอง 1K8 หลายเดือนก่อน
Ep 27. ServiceNow Reports Record Earnings from GenAI
Ep 26. Build an Open Source LLM RAG for Your Code - Ground Crew
มุมมอง 2.3K8 หลายเดือนก่อน
Ep 26. Build an Open Source LLM RAG for Your Code - Ground Crew
Ep 25. Accelerate Your Gen AI Project with MVPs & Evaluation Frameworks
มุมมอง 1.5K8 หลายเดือนก่อน
Ep 25. Accelerate Your Gen AI Project with MVPs & Evaluation Frameworks
Launch Your First Generative AI Product in 5 Weeks
มุมมอง 1.1K8 หลายเดือนก่อน
Launch Your First Generative AI Product in 5 Weeks
Ep 24. How to Rapidly Prototype Generative AI Solutions
มุมมอง 1.7K8 หลายเดือนก่อน
Ep 24. How to Rapidly Prototype Generative AI Solutions
Ep 23. Five Criteria for Selecting Your Best Generative AI Project
มุมมอง 1.5K9 หลายเดือนก่อน
Ep 23. Five Criteria for Selecting Your Best Generative AI Project
Ep 22. Transform Compliance with LLM RAGS
มุมมอง 2.1K9 หลายเดือนก่อน
Ep 22. Transform Compliance with LLM RAGS
Ep 20. Five UX Tips for Generative AI
มุมมอง 23K10 หลายเดือนก่อน
Ep 20. Five UX Tips for Generative AI
Ep 19. Build a RAG Demo in 1 Hour with GPTs
มุมมอง 5K10 หลายเดือนก่อน
Ep 19. Build a RAG Demo in 1 Hour with GPTs
Ep 18. Discover AI Opportunities with Generated Data
มุมมอง 1.1K10 หลายเดือนก่อน
Ep 18. Discover AI Opportunities with Generated Data
Ep. 17 - Intro to Retrieval Augmented Generation (RAG)
มุมมอง 10K10 หลายเดือนก่อน
Ep. 17 - Intro to Retrieval Augmented Generation (RAG)
Ep 16. Case Study: Vericant Releases GenAI Solution in 30 Days
มุมมอง 1.2K11 หลายเดือนก่อน
Ep 16. Case Study: Vericant Releases GenAI Solution in 30 Days
Can we use this for open soruce locally hosted Ollama models ?
Front Page! Suddenly repressed trauma coming up
I’ve tried to get it to do my job for me! But it can’t. 😂
Im learning, but i want to start simple, though, and understand the code as much as possible. I wish there was a good rag tutorial with full code explanatipn.
Hello sir are you looking for a professional TH-cam thumbnail designer and video SEO expert?
I totally agree. Yesterday, I created a RAG project and added transcripts from all the videos of a certain TH-camr who has over 1,000 videos. However, when I tested it, the answers were vague and unclear, which defeated the entire purpose of building the project. I wanted to understand the concepts the creator explained in his videos, but I never could. RAG failed in that aspect.
This happens in every RAG project. Did you attempt to quantify "the answers were vague?" That is the starting point. Start with a set of questions and expected answers organized in a spreadsheet. Then generate answers and paste them into your spreadsheet. Identify where it is falling short and why. You will make faster progress if you also capture the context from the original transcripts - then you can evaluate whether the LLM is getting confused via reasoning limitations, or whether it isn't getting the right context. See the performance report github.com/prolego-team/pdd/blob/main/Example-RAG-Formula-1/Performance-Report/Performance%20Report.md - download and look at the spreadsheet for an example.
Вы описали действительно интересную идею для говорящего ассистента! Чат-бот или голосовой помощник с возможностями, которые вы упомянули, мог бы значительно улучшить опыт геймеров и упростить управление модами и техническими проблемами. Вот несколько ключевых функций, которые могли бы быть полезны в таком ассистенте: Загрузка контента: Ассистент мог бы анализировать веб-страницы и загружать нужные файлы, автоматизируя процесс скачивания модов. Установка модов: Простая команда для установки модов без необходимости вручную перемещать файлы или изменять настройки. Оптимизация производительности: Ассистент мог бы автоматически настраивать параметры игры и модов, чтобы избежать лагов. Например, он мог бы управлять конфигурацией графики, разрешения экрана и настройками производительности. Решение проблем: В случае возникновения ошибок или багов, ассистент мог бы предлагать решения, корректировать конфигурацию или даже устранять неполадки автоматически. Обеспечение актуальности системы: Регулярные проверки состояния системы, обновление драйверов и программ, а также удаление ненужного ПО для поддержания производительности компьютера. Поддержка и консультации: Вопросы о том, как использовать моды, решение распространенных проблем и предоставление учебных материалов для новичков в моддинге. Такой ассистент мог бы значительно упростить взаимодействие с играми и модами, а также сэкономить время игроков. Хотя реализация такого проекта требует значительных технических усилий и ресурсов, это было бы замечательное достижение в мире геймеров!
Info on Scatchpads and overcoming LLM context window limitations: www.prolego.com/reports/report-conquering-llm-context-window-constraints
Thank you Shanif! Follow him at www.linkedin.com/in/shanifdhanani/ and check out Locusive, www.locusive.com/
Very insightful. For someone with Data Engineering and Architecture skills, I think that optimizing the data model in the backend would greatly help address this. For example, you could use optimized data marts and table partitioning. Is this a solution?
Yes, definitely. If you're willing to make data and infrastructure investments, then pretty much anything in AI is much easier. We've talked to some companies who are creating new flattened db tables so that everything fits in the LLM context. Unfortunately this type of data work can get really, really expensive to build and maintain. As LLMs get better, it will be more economical to offload as much data analysis to the LLM instead of making these investments. But we're not there yet.
What are some interesting interfaces for LLMs you have seen recently?
Thank you for the videos
Thanks for sharing good insights. I wonder my database written in foreign languages still working well with complex queries. Should I match column names to English individually?
The fact that this video of yours has less views than some others is wild. Thanks for the straightforward and direct instructions
I recently read about RAG which is retrieval augmented generation. It proposes to deal with large contextual data like documents by converting them into vector databases, we also convert our prompt into a vector embedding and then find the relevant vector embeddings from within the huge document. Then this retrieved information is added as context to the prompt rather than the entire huge database. This seems to be applicable in your case as well. Is there a reason why you decided to not go that way?
Who is running the SQL qury?
Great chat, love the focus on clarifying why coding with LLMs are different and also the authenticity with both you guys!
Thanks Kevin! I love your content. Great video!
This sounds great! How do I know this framework is authoritative?
What do you mean by "authoritative?" This is what we're doing for our client projects. What is the alternative?
Really good advice thank you for sharing your process!
Fraud Detection: Advanced analytics tools in SmythOS improve fraud detection systems by analyzing transaction patterns and identifying anomalies with greater accuracy.
Fraud Detection: Advanced analytics tools in SmythOS improve fraud detection systems by analyzing transaction patterns and identifying anomalies with greater accuracy.
Golden advice
Great advice
Thank you! This channel is a Godsend!
Not valid anymore with the new GPT models.
Why is that?
wow, just wow!
I used RAG in TH-camr's AI Telegram bot. Created a lot of AI processed character data, with fine-grained segments. The prompt itself is also crafted according to the latest Claude prompt discovery. The most amazing AI life coach experience for me yet. JulienHimselfBot
Cute, but how would this work in production with, say, very large data sets. Or with 2-3 data files we needed to combine?
This video series is literally saving my career. Thank you for your thoughtful delivery of all things AI. 5 stars on yelp!
@eclecticshenanigans - we love hearing that! Thanks for sharing!
Your contenr on LLM based application are gold mines🎉🎉🎉
@vineetsingh4042 - glad you enjoy our work!
Thanks for this insightful overview.
Our pleasure!
Does it support ollama models running in local?
i don't know how sam gets away saying the most obvious thing as if there is some nugget of wisdom there.
Love how this 4 min was spent thank you for cutting to the chase.. instant subscribe !
Thanks for the sub!
Just came across your channel and it is a gold mine. I'm learning a lot from you. Thank you.
Glad you found us! Let us know if there's ever a specific question you'd like us to address.
Never explained anything related to title 😂
Promo'SM
The challenge is not thet they do not believe in the technology, they have data security concerns which any amount of prototying will not convince them about. What they need is some authority to tell them that data sent over LLM's will not be used to re-train the data on LLM's
Great way! Does this killer app relevant even after 8 months now ? I have a problem that needs a solve like this. What is your mind state after 8 months ?
I was wondering if you have some suggestions on optimizing the documentation being used for RAG. We're using RAG linked to our Notion 'wiki', and I want to implement guidelines for the info being added, to ensure it is 'ai friendly'.
Best advice on this topic!
Wow, what a great conversation, thank you! First time viewer, typed "using rag for a codebase" into Google and your video showed up, and I'm so glad it did. Honestly, anyone who doesn't how visionary this video is - they are just not getting it. Have you seen @indydevdan? You guys are awesome, all the best 💪
i love your guys' content!! please continue to make them - it's helping me make a lot of decisions behind my ai apps
I just crashed into a wall 😂 building a demo with langchain it was so expensive and still using open ai in background. That why I came across this video, my search was “langchain is not profitable “ and you are the first explaining why. Thanks, I’m loving your videos.
in other words, ship in 2 years instead of 2 weeks.
If frameworks help you ship faster, then by all means use them. In our experience they don't, and most teams ship slower because of troubleshooting the interface. But YMMV.
@@prolegoinc I will agree that there are different philosophy in software development. But with the exponentially of AI LLM development progress, I don't believe the old way of vertical skill of an expert is valid any more. What is truly needed is someone to become a true jack of all trades of a horizontal approach that knows all tools and frameworks out there and writing high level code "instruction" and a quick time to market approach. I am speaking from a 27 years working on software developer on both Java and C# background.
This brother does not blink ☠️☠️☠️ gtfo of here with this bullshit. You could say the wisest things in this video but the fact that its 100% AI generated just makes it complete shit. Delete your channel please and rethink your life choices
Man you are paranoid. Even if it's AI, the information is useful
@@lhxperimentalyeah no. Its a cashgrab and trying to make easy money. that is my problem. There is nothing genuine about it just „pump out as much content as fast as possible“. That is my problem with it, but you NPC wouldnt understand. Listen to your NPC content written by literally another NPC.
Great discussion. Thanks for sharing this
You miss under the meaning of "New knowledge", this specifically means vectors representing a concept that doesn't exist in the training set. Most vectors already exist, most "knowledge" is not new, and fine-tuning allows the model to focus and improve accuracy. Fine-tuning is not something to teach a model new tricks - this is called extended pretraining. Fine-tuning allows a company to bring to the surface latent capabilities
thank you 🙌