In this podcast episode on The Democratization of Machine Learning, Lauren Hawker Zafer talks to Julien Simon, Chief Evangelist at Hugging Face. The company is an AI community whose mission is to democratize machine learning. Its drive has been met by great interest and has allowed Hugging Face to reach $100 million in investments this month, boosting its net worth to an estimated $2 billion.
Making Machine Learning (ML) accessible to the point where developers and business people use and spread it, thereby creating outstanding products and services with it, is at the heart of Hugging Face’s mission.
Human or Machine – or Both?
Awareness is key when it comes to promoting the widespread use of a technology whose potential influence is as vast as that of Machine Learning. One area that needs to receive awareness is potential issues with models, such as the inclusion of biased data. Another issue that deserves attention is the question of when to outsource tasks to machines and when to keep them in the hands of humans. Automating tasks usually also means scaling them and generating bigger outputs, which is why one should think twice before applying ML models in critical areas – e.g. when human lives are involved. That means that machines won’t operate completely without humans for the foreseeable future.
Is ML Magically Simple?
While ML may look like magic, it involves many areas from math to computer science and statistics, to data analytics and software engineering, and much more. Its complexity needs to be simplified in order to make it available to as many people as possible and to, eventually, make it as invisible and widespread as electricity or running water. Finally, allowing ML to make people’s life easier and to create tailored customer experiences is where the real magic lies.
Want to build your own Machine Learning Model and publish it on Hugging Face? Then head to The Squirro Academy to start building.
You can also try out one of Squirro’s models on Hugging Face by following this link.
Once you have built your model, you can run it on Squirro’s Model Service – Model As A Service. Head to our documentation to find out more.
No-Code or Full Code – Squirro’s Machine Learning Ecosystem has everyone covered!