Oxford Adventures and OxML 2025

22 August, 2025

Oxford Adventures and OxML 2025

Photos from my visit to Oxford and reflections on presenting at OxML Summer School 2025

This August, I was invited to speak at the OxML Summer School 2025, held at the University of Oxford. The event was a fantastic opportunity to share my insights on machine learning and connect with fellow enthusiasts in the field. It was also a chance for me to visit the beautiful city of Oxford, known for its rich history and stunning architecture.

Embarking on the Journey

My departure was from Paris Gare du Nord, heading to London St Pancras via the Eurostar.

Upon arriving in London, my first stop was the Google Office in London. The office is located in the heart of the city, and I was impressed by its modern design and vibrant atmosphere. Nghia Le was kind enough to give me a tour of the office, and we had a great time catching up in the Google cafeteria.

After the tour, I headed to Oxford. The train ride from London to Oxford was smooth and comfortable, allowing me to take in the scenic views of the English countryside.

After checking into my hotel, it was a bit late in the afternoon, so I decided to take a leisurely walk around the city center.

For dinner, I went to a Thai restaurant nearby. The food was delicious, and I enjoyed the cozy atmosphere of the place.

First Talk at OxML

My first talk was on August 5th, with the theme "Health & Bio". It was a high-level talk where I introduced the project that I'm working on, llama.cpp. The talk was well-received, and I had the opportunity to engage in some interesting discussions with the attendees.

The recording is available on Elandi, though unfortunately it's not available for public viewing. But in case you're interested, you can check out the slides from my talk.

While being inside the campus, I found a quiet place to relax and take some photos.

On the way back to the hotel, I took some photos of the beautiful architecture and charming streets of Oxford.

Walking Around Oxford

On my third day in Oxford, I decided to go a bit further out to explore more of the city.

The first destination was the University Park. The park is a peaceful oasis, with beautiful green spaces and walking paths. I spent some time wandering around, taking in the sights and sounds of nature.

Then, I headed back to the city center to visit the Sheldonian Theatre. There were quite a lot of tourists, so I enabled the long exposure mode on my camera to capture some interesting light trails from the moving people.

Next, while searching for a place to have dinner, I stumbled upon the Tirah Memorial.

Second Talk at OxML

My second talk was on August 7th, with the theme "Representation Learning". This time, I delved deeper into the technical aspects of multimodal models, discussing the challenges and opportunities in this rapidly evolving field.

The talk was well-attended, and I received some great questions from the audience. It was a pleasure to share my knowledge and experiences with such an engaged group of learners.

The recording is also available on Elandi, but again, it's not publicly accessible. My talk was an extended version of my blog post about multimodal models, which you can read here. Alternatively, last month, I gave a similar talk at the AI Plumbers Conference. You can watch it here.

London Layover

On my last day, I had a layover in London before heading back to Paris. I decided to make the most of my time by visiting a few iconic landmarks around Pancras Square.

I took quite a lot of photos around the Regent's Canal, capturing the serene waterway and the charming boats docked along the sides.

Final Reflections

Overall, my trip to Oxford and participation in the OxML Summer School 2025 was an enriching experience. It was a perfect blend of professional growth and personal exploration, allowing me to connect with like-minded individuals while immersing myself in the beauty of Oxford. I'm grateful for the opportunity and look forward to future events where I can continue to share my passion for machine learning.

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