WEBINAR ON DEMAND: QUANTS CAN GET ENOUGH
MIMD Architecture and Opportunities for AI/ML Optimisation in Finance using IPUs
To date accelerations of algorithms have revolved around SIMD architecture GPGPU, causing many classes of problems to be ‘rephrased’ in a manner to suit it. They work well, but when state needs to be considered, such as MCMC (Markov Chain Monte Carlo), natural language processing, neural net modelling and many other increasingly distributed, federated, forms of calculations, other novel approaches such as MIMD need to be considered.
Our experts will discuss how the Graphcore Intelligence Processing Unit (IPU) enables finance firms to use models of greater complexity and iterate faster than is currently possible with legacy processors.
In this webinar you’ll learn:
• How to achieve faster financial model accelerations
• How to use IPUs for financial modelling training and inference
• Insights into advanced models, use cases and benchmarks
• Demonstration of the latest MK2 IPU technology
REGISTER TO WATCH ON DEMAND
PRESENTERS
Andrew Addison
Andrew Addison is a senior software engineer with nearly 30 years of experience in the financial services industry. He graduated in Computational Science at St. Andrews University in 1990 and spent several years working in core development for a 4GL company specialising in compiler writing. With a deep understanding of technology Andrew has developed and deployed high volume distributed computational solutions for major investment banks such as Salomon Brothers, JP Morgan, Merrill Lynch, SwissRe, Bank of America, Deutsche Bank and also number of well-known hedge funds.
Alex Tsyplikhin
Alexander Tsyplikhin is a Senior AI Engineer at Graphcore. Qualified to PhD level in Speech Biometrics, Alexander has worked in the field of machine learning for 19 years. He is passionate about leveraging technology and innovation to improve lives and generate results for businesses.
At Graphcore, Alexander is focused on AI use cases in industry, using his expertise in machine intelligence to help drive customer success.
IPU APPLICATIONS
ALGORITHMIC TRADING
To forecast market activity with speed and accuracy, traders are increasingly turning to next generation models. IPUs enable you to harness recent innovations so you can identify and act on complex trade signals in real time.
FRAUD DETECTION
Acting on threats as soon as they arise is critical to safeguarding financial security. By running complex ML models on the IPU, you can tackle these outliers at the earliest stage without jeopardising customer experience.
INVESTMENT MANAGEMENT
Smart investment means outmanoeuvring market fluctuations. The IPU enables you to accelerate derivative pricing models and leverage alternative data faster to improve sentiment analysis and increase revenue.
RISK MANAGEMENT
New machine learning algorithms can help prevent fraud and predict market shifts – but they are also compute-intensive. The IPU helps you to fully utilise recent AI approaches to proactively track, anticipate and manage risk.
In Partnership with:
The Level39 fintech Thalesians Ltd is a neocybernetics company using the new science and technology to revolutionize finance, insurance, transportation, shipping, and medicine in the United Kingdom and worldwide.
We do this by implementing real-time ML/AI software for neocybernetic systems, providing education, and consulting services.
We are experts in the application of ML/AI techniques to time series data, particularly Big Data and high-frequency data. Our areas of expertise include the mathematics of ML/AI, Deep Learning (DL), Python, and kdb+/q.
In Partnership with:
Advances in machine intelligence are transforming the finance sector. New approaches to AI are enabling innovators to get ahead of global economic shifts, forecast market volatility and increase investment returns. With the IPU, quantitative researchers can harness state of the art compute to explore and create new algorithms that have the potential to redefine financial services.