Kyrgyzstan to King’s Cross: the star baker cooking up code

My day can vary, it really depends on which phase of the project I’m on. Let’s say we want to add a feature to our product – my tasks could range from designing solutions and working with the team to find the best one, to deploying new features into production and doing maintenance. Along the way, I’ll communicate changes to our stakeholders, write docs, code and test solutions, build analytics dashboards, clean-up old code, and fix bugs.Read More

Kyrgyzstan to King’s Cross: the star baker cooking up code

My day can vary, it really depends on which phase of the project I’m on. Let’s say we want to add a feature to our product – my tasks could range from designing solutions and working with the team to find the best one, to deploying new features into production and doing maintenance. Along the way, I’ll communicate changes to our stakeholders, write docs, code and test solutions, build analytics dashboards, clean-up old code, and fix bugs.Read More

Dynamic language understanding: adaptation to new knowledge in parametric and semi-parametric models

To study how semi-parametric QA models and their underlying parametric language models (LMs) adapt to evolving knowledge, we construct a new large-scale dataset, StreamingQA, with human written and generated questions asked on a given date, to be answered from 14 years of time-stamped news articles. We evaluate our models quarterly as they read new articles not seen in pre-training. We show that parametric models can be updated without full retraining, while avoiding catastrophic forgetting.Read More

Dynamic language understanding: adaptation to new knowledge in parametric and semi-parametric models

To study how semi-parametric QA models and their underlying parametric language models (LMs) adapt to evolving knowledge, we construct a new large-scale dataset, StreamingQA, with human written and generated questions asked on a given date, to be answered from 14 years of time-stamped news articles. We evaluate our models quarterly as they read new articles not seen in pre-training. We show that parametric models can be updated without full retraining, while avoiding catastrophic forgetting.Read More

Building a culture of pioneering responsibly

When I joined DeepMind as COO, I did so in large part because I could tell that the founders and team had the same focus on positive social impact. In fact, at DeepMind, we now champion a term that perfectly captures my own values and hopes for integrating technology into people’s daily lives: pioneering responsibly. I believe pioneering responsibly should be a priority for anyone working in tech. But I also recognise that it’s especially important when it comes to powerful, widespread technologies like artificial intelligence. AI is arguably the most impactful technology being developed today. It has the potential to benefit humanity in innumerable ways – from combating climate change to preventing and treating disease. But it’s essential that we account for both its positive and negative downstream impacts.Read More