Sitemap

A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.

Alas, Page Not Found

Page not found. Your pixels are in another canvas.

Samuel Albanie

Posts

digests

Anonymisation in egocentric video

A video digest of research related to anonymisation in egocentric video.
Topics: computer vision, privacy
Date: April, 2022
[slides]
 

Neural network architectures, scaling laws and transformers

Summary: A video digest of ideas related to neural network architectures, scaling laws and transformers.
Topics: neural network architectures, scaling laws, transformers
Date: April, 2022
[slides]
 

Contrastive Language-Image Pre-training (CLIP)

Summary: A video digest of the CLIP research paper.
Topics: computer vision, zero-shot learning, vision and language
Date: April, 2022
[slides]
 

Self-supervised learning and pseudo-labelling

Summary: A video digest of research ideas related to self-supervised learning and the pseudo-labelling algorithm.
Topics: computer vision, self-supervised learning, pseudo-labelling
Date: April, 2022
[slides]
 

Flamingo: a Visual Language Model for Few-Shot Learning

Summary: A video digest of the Flamingo research paper.
Topics: computer vision, few-shot learning, vision and language
Date: May, 2022
[slides]
 

DINO: Self-distillation with no labels

Summary: A video digest of the DINO research paper.
Topics: computer vision, few-shot learning, vision and language
Date: June, 2022
[slides]
 

Querybank normalisation (QB-Norm)

Summary: A video digest of the QB-Norm research paper.
Topics: vision and language, hubness, cross modal retrieval
Date: June, 2022
[slides]
 

On the Opportunities and Risks of Foundation Models (introduction)

Summary: A slow video description of the introduction to the Foundation Models report from Stanford.
Topics: foundation models, emergence, homogenisation
Date: June, 2022
[slides]
 

Language Models are Few-shot Learners (GPT-3)

Summary: A slow video description of the GPT-3 research paper.
Topics: language models, foundation models, GPT-3, scaling
Date: July, 2022
[slides]
 

Evaluating Large Language Models Trained on Code (Codex)

Summary: A slow video description of the Codex research paper.
Topics: codex, language models, foundation models, coding
Date: July, 2022
[slides]
 

Why numbering should start at zero (according to Dijkstra): Samuel’s guide

Summary: Samuel's tutorial on Why numbering should start at zero by Edsger W. Dijkstra, published in 1982 as EWD 831.
Topics: Dijkstra, counting, programming conventions
Date: September, 2022
[slides]
 

Row-major vs column-major: Samuel’s guide

Summary: Samuel's tutorial on row-major and column-major ordering for multi-dimensional array storage.
Topics: computing, memory, arrays
Date: September, 2022
[slides]
 

🤗 Datasets: A community library for natural language processing

Summary: A description of the 🤗 Datasets library, as summarised by Q. Lhoest et al. in their EMNLP 2021 demo paper.
Topics: Hugging Face, machine learning, NLP
Date: September, 2022
[slides]
 

PromptSource - an IDE and repo for natural language prompts

Summary: A description of PromptSource: An Integrated Development Environment and Repository for Natural Language Prompts by S. Bach and others under the BigScience project as a demo at ACL 2022.
Topics: Prompting, annotation tools, NLP
Date: September, 2022
[slides]
 

Hash tables: Samuel’s guide

Summary: Samuel's tutorial on the hash table data structure.
Topics: Hash tables, data structures, algorithms, coding
Date: September, 2022
[slides]
 

Big O notation: Samuel’s guide

Summary: Samuel's tutorial on big O notation and other asymptotic notation (little o, big theta, big omega, little omega).
Topics: Complexity, data structures, algorithms, analysis
Date: October, 2022
[slides]
 

ReCo: Retrieve and Co-segment for Zero-Shot Transfer

Summary: A short description of the ReCo framework introduced in the work 'ReCo: Retrieve and Co-segment for Zero-shot Transfer' by G. Shin, W. Xie and S. Albanie, published at NeurIPS in 2022.
Topics: semantic segmentation, foundation models, zero shot transfer
Date: October, 2022
[slides]
 

Scaling Instruction-Finetuned Language Models (Flan-PaLM)

Summary: A description of the the work 'Scaling Instruction-Finetuned Language Models' by Hyung Won Chung et al. published on arxiv in October 2022. This work introduced the Flan-PaLM 540B model.
Topics: instruction finetuning, foundation models, large language models
Date: October, 2022
[slides]
 

Binary Search Trees: Samuel’s guide

Summary: Samuel's tutorial on the binary search tree data structure.
Topics: Binary search trees, data structures, algorithms, coding
Date: October, 2022
[slides]
 

Crosslingual Generalization through Multitask Finetuning (BLOOMZ & mT0)

Summary: A description of the the work 'Crosslingual Generalization through Multitask Finetuning' by Niklas Muennighoff et al. published on arxiv in November 2022 as part of the BigScience Workshop. This work introduced the BLOOMZ and mT0 models.
Topics: multitask finetuning, foundation models, large language models, multilingual models
Date: November, 2022
[slides]
 

Red-black trees: Samuel’s guide

Summary: Samuel's tutorial on the red-black tree data structure.
Topics: Red-black trees, data structures, algorithms, coding
Date: December, 2022
[slides]
 

B-trees: Samuel’s guide

Summary: Samuel's tutorial on the B-tree data structure.
Topics: B-trees, data structures, algorithms, coding
Date: December, 2022
[slides]
 

Heapsort and Binary Heaps: Samuel’s guide

Summary: Samuel's tutorial on Heapsort and the binary heap data structure.
Topics: Heapsort, binary heap, priority queue, data structures, algorithms, coding
Date: December, 2022
[slides]
 

Quicksort: Samuel’s tutorial

Summary: Samuel's tutorial on the quicksort algorithm.
Topics: Quicksort, sorting, algorithms, coding
Date: January, 2023
[slides]
 

Comparison Sorting Lower Bounds: Samuel’s tutorial

Summary: Samuel's tutorial on lower bounds on the fastest possible comparison sorting algorithms.
Topics: lower bounds, sorting, algorithms, coding
Date: January, 2023
[slides]
 

Counting Sort: Samuel’s tutorial

Summary: Samuel's tutorial on counting sort.
Topics: sorting, algorithms, coding
Date: January, 2023
[slides]
 

Radix Sort: Samuel’s tutorial

Summary: Samuel's tutorial on counting sort.
Topics: radix sort, sorting, algorithms, coding
Date: January, 2023
[slides]
 

BLOOM: A 176B-Parameter Open-Access Multilingual Language Model

Summary: A description of the the work 'BLOOM: A 176B-Parameter Open-Access Multilingual Language Model' by Le Scao et al. published on arxiv in November 2022 as part of the BigScience Workshop. This work provides an overview of the BLOOM model and the efforts involved in its creation.
Topics: foundation models, large language models, multilingual models
Date: January, 2023
[slides]
 

Bucket Sort: Samuel’s tutorial

Summary: Samuel's tutorial on bucket sort.
Topics: bucket sort, sorting, algorithms, coding
Date: January, 2023
[slides]
 

Task-parallel computing: Samuel’s tutorial

Summary: Samuel's tutorial on task-parallel computing.
Topics: Task parallelism, data parallelism, Moore's law, Dennard scaling, Amdahl's law, Gustafson's law
Date: February, 2023
[slides]
 

What is the alignment problem?

Summary: A short description of What is the alignment problem? by Jan Leike.
Topics: AI alignment, capabilities, the hard problem of alignment
Date: March, 2023
[slides]
 

NP-complete problems: Samuel’s tutorial

Summary: Samuel's tutorial on NP-complete problems.
Topics: P versus NP, decision problems, verification algorithms, NP-completeness
Date: February, 2023
[slides]
 

GPT-4

Summary: A description of the GPT-4 technical report by OpenAI.
Topics: GPT-4, Large Language Model, Capabilities, Risks
Date: March, 2023
[slides]
 

Large Language Models are Few-Shot Publication Scoopers

Summary: A summary of the SIGBOVIK 2023 paper, Large Language Models are Few-Shot Publication Scoopers.
Topics: Scooping, Large Language Models, SIGBOVIK
Date: March, 2023
[slides]
 

Computer Vision: A very short introduction

Summary: A very short introduction to the field of computer vision.
Topics: Computer Vision, introduction, tasks
Date: April, 2023
[slides]
 

AI News (24th April 2023)

Summary: A short summary of recent AI-related news.
Topics: AI news
Date: April, 2023
[slides]
 