5 Types of AI Company - Explained!! 

Love the concept for this video. Thank you!

Im watching this because im making a RAG using OLLAMA and local LLM, its quite challenging but im sure will be worth it

Mistral, Cohere, SAP, META, Anthropic, Google, OpenAI, Alibaba.. some middle eastern companies. OH yeah Hugging Face watched a excellent talk on how they built a Code LLM.

00:01 Different types of AI companies explained 01:57 Foundational model innovators are R&D companies building large AI models. 06:10 Different types of AI companies explained 08:06 Companies fine-tune existing AI models for their own use cases. 12:25 AI companies are heavily burning VC money in competitive space 14:41 Be cautious about joining AI companies with heavy offers 18:29 Building a solid infrastructure is essential for managing AI models efficiently 20:18 AI companies need builders for sustainable software systems. 24:06 Understanding Standalone and Integrated AI Products 26:11 Starting an AI company with a specific problem 29:47 Building AI applications for niche markets adds actual value 31:30 Building application layer is crucial for AI companies 35:05 Different types of AI companies explained

Your videos are always insightful

Loved the video. Made me think in a lot of ways I normally wouldn’t

Bless you. I think it is an accurate and useful hierarchy. The growth areas for most engineers is adaptive fine-tuning and general open source model wrangling ...LoRA for sure, but also adding vision transformers, creating mixtures, etc.

Any tip for experienced software engineer who looking for change in AI and ML space which type of company and role should be looking for. What skills should develop before we start applying? Self learned basic model fine tuning using hugging face and still learning… Really nice video ❤

Very valuable content shared in this video Thanks!

May Allah bless you brother, you are realy delivering with your content

really liked the video

More helpful thanks❤

Nice informative video.

Building out infrastructure and integrating AI/mlops into production is probably the most important part. A lot of people can test llms and configure test environments. Placing in existing production is different story.

plz plz don't stop making this kind of videos , make more these type of videos

great video valuable time❤

bhai best video

love it , where is the end part companies list website??

Gold Video! Thanks for compilation of the ideas. But, I might say that I am a bit distracted because of your left hand.

very interesting video.

Jamba - by AI21 labs based on Mamba structure

I want the US government to collect all private data of its citizens through OpenAI 🇺🇸, and the US government should completely take over SOTA models to do e-acc 🚀

Can you make more video on standalone Ai for react , mern developers As most of standalone Ai RU-vid video just talk about voiceflow, stack ai no code tools platform

🎯 Key points for quick navigation: 00:00 *🚀 Introduction and Purpose* - Overview of the video's intent and audience, - Introduction to the "FACES" framework for categorizing AI companies. 01:37 *📚 Explanation of the FACES Framework* - Breakdown of the FACES acronym, - Introduction to each category within the framework. 02:19 *🧠 Foundational Model Innovators* - Description of companies building base AI models, - Examples like OpenAI and Google DeepMind, - Emphasis on the R&D focus and resource intensity. 06:46 *🔧 Adaptive Fine Tuners* - Companies that adapt foundational models for specific uses, - Examples of companies like Salesforce, - Explanation of the fine-tuning process and necessary resources. 11:53 *🌐 Convenient API Providers* - Companies offering APIs for easy model deployment, - Discussion of market competition and business models, - Examples include Replicate and Fireworks. 17:31 *🏗️ Essential Infrastructure Builders* - Importance of infrastructure for AI deployment, - Examples of companies providing tools for monitoring and deployment, - Discussion of the essential nature of this category in AI ecosystems. 21:04 *🛠️ Essential Infrastructure Builders* - Importance of infrastructure in AI product development, - Requires more software engineers than AI engineers, - Includes roles like kernel programmers and solution architects. 24:33 *🧩 Standalone and Integrated AI Products* - Types of AI products: standalone and integrated, - Examples of integrated products like Notion AI, - Examples of standalone products like Jasper for copywriting. 26:49 *💡 Opportunities in AI Product Development* - Building niche AI products for specific domains, - Importance of identifying specific problems and solutions, - Potential for quick profits with low initial investment. 30:33 *🏆 Market and Investment Dynamics* - VCs' skepticism and market competition, - The importance of unique selling propositions (USPs) in AI products, - Examples of companies and their market positioning. 34:15 *📝 Summary and Final Thoughts* - Recap of the FACES framework, - Importance of different layers in the AI ecosystem, - Encouragement to innovate in various AI product domains. Made with HARPA AI

Isn't AI wrapper and standalone Product company one and the same thing?

Great Video as usual! BTW What's on your left hand?

❤

I am surprised u did not mention Anthropic as Foundation Model Innovators

What is your advice to one undergrad learning GenAI specifically to get placed?

Bro, can you please do a video on liquid neural networks in detail😅

hugging faces , atari , nvidia

Other than OpenAI? BLOOM (BigScience Large Open-science Open-access Multilingual Language Model) Although not a "company", more of a consortium. Its 176B open source model (1.7T token) is the basis for Bloomberg's closed source BloombergGPT Finance AI model.

Bro I must ask, what's wrong with your hand?

Nice informative video.