EdgeAI: The Strategical future of AI for Low and Middle Income Countries 9885
Years ago I was urging LMICs like Morocco to get into AI quickly, that was before ChatGPT. Today I am assisting to a great talk by Danilo Pau at SophI.A Summit 2024 explaining why the current trends in AI are insane.
ChatGPT is a major historical turning point. With ChatGPT, the general public started seriously caring about AI, driving unprecedented amounts of revenues. It is also the historical turning point towards *very large* LLMs. The post-ChatGPT world is a very different world: state-of-the-art AI has become extraordinary expensive, pricing most countries our of the race because expensive hardware and energy.
If the current AI trends continue, powerful AI development will only be possible in a few countries, relegating everyone else to AI consumers. In this context EdgeAI presents an interesting potential solution.
EdgeAI is AI on the edge, it means using small components and sensors to do more of the AI heavy lifting. Instead of having a camera only take pictures before sending them to am AI Cloud, part of the AI could be ran into the camera itself by specialized hardware. This means a much lower cost for hardware and energy. It is a type of AI that can be distributed and could be deployed with much lower means.
Challenges for EdgeAI are nonetheless many. First of all, there is interest, most of the AI community is focusing on ever bigger models. Then, EdgeAI requires the development of specialized hardware, this hardware will have to be imagined and software will have to be written to ensure compatibility with mainstream AI software.
EdgeAI also requires a specific set of skills: __**Old School Skills**__. Today, most computer science students spend most of their time working with scripting languages like Python and Javascript. These are what's called *high level* languages, *high level* means easy, it means the thinking required to interface with the hardware is done for you. The corollary is that the basics of data-structure, algorithmic, machine language and information theory are often lacking; because not practiced and not needed for cloud computing. These are the exact skills needed to make EdgeAI a reality.
Here lies a new opportunity in AI: focus on the development of EdgeAI and adapt the curricula to the needs of EdgeAI. Develop solutions that are not only adapted to local markets, but will also be competitive on the global market because they are cheaper more effective and reliable.
#SophIA2024
Vous quittez Bluwr.
Nous ne pouvons pas garantir ce qui se trouve après ce lien