Privacy Enhancing Technologies (PETs) | What are PETs | Examples

David Friend joins Bitfount as Head of Business Development

We are excited to announce that David Friend has joined Bitfount as our Head of Business Development. David will be responsible for defining and owning the company’s commercial strategy, working to expand Bitfount’s footprint in the AI-driven healthcare and clinical trial space.

Bitfount Partners with Milner Therapeutics Institute for Innovative Collaborations in the Healthcare Sector

Bitfount has joined forces with the Milner Therapeutics Institute at the University of Cambridge as an Affiliate Company. This partnership opens up a world of opportunities for our organisations to collaborate and drive innovation in HealthTech.

TRE-FX | UK's Trusted Research Environment Project | Secure data collaborations

The TRE-FX project aimed to address challenges associated with executing data analysis across multiple TREs with differing geographical or governance boundaries.

RETFound | Easiest way to use RETFound | AI for eye | OCT AI

RETFound, developed by researchers at Moorfields Eye Hospital and University College London, is the world's first foundation model trained on retinal images (retinal foundation model). RETFound can be accessed through Bitfount's no-code platform.

Welcoming Sajan Khosla to Bitfount's advisory board

We're excited to announce that Sajan Khosla has joined Bitfount's advisory board. Read the full announcement below.

Federated Machine Learning | Privacy-Enhancing Technologies PETs

Federated Learning (FL) is simply a Machine Learning (ML) setting where many clients collaboratively train a model under the orchestration of a central server while keeping the training data decentralised.

Machine Learning Model Evaluation | Federated Machine Learning | Privacy-Enhancing Technologies PETs

Federated ML model evaluation allows you to send a trained ML model you wish to evaluate to the data, rather than requiring the data to be centralised first.

Secure Multiparty Computation | Multiparty Computation | Privacy-Enhancing Technologies PETs

Secure multiparty computation (MPC / SMPC) is a cryptographic protocol that distributes a computation across multiple parties where no individual party can see the other parties’ data.

Trusted Execution Environments | Privacy-Enhancing Technologies PETs

Trusted Execution Environments are one mechanism for enabling multiple parties to collaboratively do computation. The security depends on the computation running in an environment that all the parties trust.

Homomorphic Encryption Guide | Fully Homomorphic Encryption | Privacy-Enhancing Technologies PETs

Homomorphic Encryption methods are encryption schemes which allow mathematical operations to be performed on the underlying data whilst keeping the data in the encrypted space.

Tokenization | Sprint Tokenization | Data tokenization | Privacy-Enhancing Technologies PETs

Tokenization is the process through which one “substitutes a sensitive identifier (e.g., a unique ID number or other PII) with a non-sensitive equivalent (i.e., a ‘token’) that has no extrinsic or exploitable meaning or value”

Differential Privacy | Privacy-Enhancing Technologies PETs

Differential Privacy addresses the paradox of learning nothing about an individual while learning useful information about a population. Differentially private techniques protect the privacy of individual data subjects by adding random noise when producing statistics.

Welcoming Ronya Rubinstein to Bitfount’s advisory board

We are honoured to announce that Ronya Rubenstein has joined Bitfount’s advisory board. Ronya brings a wealth of experience and a unique industry perspective that aligns perfectly with our mission at Bitfount.

Bitfount Wins at CogX for Best Innovation in Pharma

We are thrilled to announce that Bitfount has been honoured with the CogX 2023 Award for Best Innovation in Pharma! The award recognises our groundbreaking work in accelerating clinical trials for new drug discovery through the use of Federated Data Science and Artificial Intelligence.

Applications of Federated Learning in Healthcare Imaging

By the World Economic Forum’s estimation, nearly 4 billion imaging procedures are performed worldwide every year with a market size of USD 40 billion in 2023. Recent advances in medical imaging have transformed patient diagnosis and treatment.

Introducing: Biswa Rout, Frontend Engineer

Meet Biswa, our brilliant Frontend Engineer! With his unwavering dedication to crafting exceptional user experiences, Biswa has been an invaluable asset to our team.

Federated Learning: Revolutionising AI by training models on distributed data without data sharing

Federated learning is reshaping the AI landscape, providing a new paradigm for training machine learning models that prioritise both data privacy and efficiency.

Ethical Considerations in AI Large Language Models

Find out how the emergence of AI and LLMs raises significant ethical concerns, particularly regarding bias, privacy, and accountability.

Demo: GA patient pre-screening using Bitfount and Altris AI's OCT segmentation model

Introducing: João Gonçalves, Software Engineer

Meet João, one of Bitfount's Software Engineers, and learn about his background and his work.

Removing the Need to Re-Invent the Wheel in Diagnostic AI Software

A historical view of how medical AI has been deployed and how Bitfount disrupts this model by enabling a "plug & play" approach to model deployment.

Bitfount awarded funding to transform clinical trials with federated data science

We’re excited to share details of funding awarded to Bitfount by Innovate UK, the UK’s innovation agency, to expand our distributed data science platform to address one of the most broken parts of global healthcare R&D.

Introducing: Blaise Thomson, CEO and Co-Founder

Meet Blaise and find out what it's like to be the CEO and Co-Founder at Bitfount

Announcing Bitfount's Open Beta Launch

Bitfount to launch open beta enabling data custodians to make sensitive data available to data scientists and researchers for privacy-preserving analysis and AI/ML.

Zero-Trust Security for Federated Learning & Analytics

An explanation of how federated learning and zero-trust are compatible concepts.

Bitfount's Aims & Architecture

How does Bitfount approach distributed data science with a novel architecture? Learn more in this article.

Introducing: Matt Seigel, Head of Engineering

Meet Matt our Head of Engineering, and find out what he does at Bitfount.

Introducing: Lauren Kaufman, Business Development

Meet Lauren and find out what it's like doing Business Development at Bitfount.

Introducing: Daniella Currie, Operations Manager

Meet Daniella and find out what it's like to be a Operations Manager at Bitfount.

Introducing: Bristena Oprisanu, Machine Learning Privacy Engineer

Meet Bristena and find out what a Machine Learning Privacy Engineer does at Bitfount.

Introducing: Ali Amin-Nejad, Machine Learning Engineer

Meet Ali, one of the Machine Learning Engineers, and find out what he does at Bitfount.

The Federated Data Science Unlock in Healthcare

Use of healthcare data is currently frustrated by valid privacy- and bias concerns. Privacy-enhancing technologies like federated machine learning and analytics can safely unlock the enormous value of healthcare data for the benefit of patients.

Announcing our seed funding round

We've raised $5M from great investors to turbo-charge our mission of giving every organisation data collaboration superpowers. Onwards!

Introducing Bitfount

Bitfount is a federated data science and AI platform. We're on a mission to give every organisation data collaboration superpowers, without compromising on privacy, speed or ease of use. Join us!

Taylor Swift AI: The Dark Side of Generative AI and Why Ethical Use of AI Matters

Generative AI is an incredibly powerful technology that can create hyper-realistic content ranging from text and images to music and deep fake videos. A notable example is the Taylor Swift AI, an AI system that mimics the voice and style of the famous pop star, producing new songs that sound remarkably authentic.

Usage-based access control policies

The value of a dataset is determined not by its existence, but by how it is actually used. Bitfount enables true usage-based access control.

Introducing: James Marchant, Machine Learning Engineer

Meet James and find out what it's like to be a Machine Learning Engineer at Bitfount.