AI research, ideas and product updates.

Why you should take a data first approach to AI

Machine learning systems are born through the marriage of both code and data. Academia mostly focuses on ways to improve the learning algorithms, the *how* of machine learning. When you come to build practical AI systems though the data-set you're training on has at least as much impact on performance as the choice of algorithm.

Raza Habib

August 2021

Blog

What is an active learning platform?

Data first ML Ops needs new kinds of tools. An Active Learning platform is a single tool that combines data annotation, model training and deployment in one continuous process.

Raza Habib

August 2021

NLP

How good is GPT-3 in practice?

We discuss the real world performance of Open AI's GPT-3 language model and speculate on what the future of large pre-trained language models may hold.

Raza Habib

July 2021

Blog

Four lessons from a year building tools for machine learning

The most surprising lessons about how to build tooling for machine learning, what is needed going forwards and why domain experts will play a much larger role in the future of AI.

Raza Habib

July 2021

Case Study

Measuring Active Learning performance in the real world

Humanloop worked with Black Swan Data, a company at the forefront of applied NLP, to test our active learning platform. Humanloop was able to save at least 40% of the labeling normally required whilst improving performance

Raza Habib

March 2021

Announcement

Humanloop + Hugging Face 🤗 = the fastest way to build custom NLP

You can now train any Huggingface model on your own data just by labeling and curating a small portion of that data, with early access to our Humanloop - Hugging Face integration. Label your data and we'll give you an API to your model, trained on your own data

Raza Habib

February 2021

Machine Learning

Why you should be using active learning to build ML

Data labeling is often the biggest bottleneck in machine learning. Active learning lets you train machine learning models with much less labeled data. The best AI-driven companies, like Tesla, use active learning.

Raza Habib

February 2021

John R.

Chartered Legal Executive

John works at one of the UKs largest legal firms. He’d been tasked with labelling over 35,000 contracts into various categories - not a fun job. But with help from Humanloop, he was able to build and train an AI model that automatically orgsanised the contracts into the correct category with a 98.7% accuracy. He completed the task in under two days, which would usually have taken over 200 hours - that’s a happy John.

Legal services

John R.

Chartered Legal Executive

John works at one of the UKs largest legal firms. He’d been tasked with labelling over 35,000 contracts into various categories - not a fun job. But with help from Humanloop, he was able to build and train an AI model that automatically orgsanised the contracts into the correct category with a 98.7% accuracy. He completed the task in under two days, which would usually have taken over 200 hours - that’s a happy John.

Customer service

John R.

Chartered Legal Executive

John works at one of the UKs largest legal firms. He’d been tasked with labelling over 35,000 contracts into various categories - not a fun job. But with help from Humanloop, he was able to build and train an AI model that automatically orgsanised the contracts into the correct category with a 98.7% accuracy. He completed the task in under two days, which would usually have taken over 200 hours - that’s a happy John.

Community management

John R.

Chartered Legal Executive

John works at one of the UKs largest legal firms. He’d been tasked with labelling over 35,000 contracts into various categories - not a fun job. But with help from Humanloop, he was able to build and train an AI model that automatically orgsanised the contracts into the correct category with a 98.7% accuracy. He completed the task in under two days, which would usually have taken over 200 hours - that’s a happy John.

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