BeyondMath
- 21/08/2024
- Seed
- $8,500,000
Simulate the physical world with AI
BeyondMath are taking an AI first approach to transforming the world of numerical simulation as used in science, engineering and design. A field that still uses decades old technology and is ripe for disruption with AI.
We are a newly funded startup that has just closed our pre-seed round.
- Industry Software Development
- Website https://beyondmath.com/
- LinkedIn https://www.linkedin.com/company/beyondmath/
Related People
Alan PattersonCo Founder
Currently working on a new startup in AI.
30 years experience in applied machine learning and software engineering. 3 out of 4 startups with successful exits, all in applying ML to real-world problems. Thought leader and enabler for innovation with a laser focus on solving the right customer problems in an effective way. Making it happen, building the teams and empowering them to be as effective as possible.
Still a hands-on coder and builder, an ML enthusiast with projects at the bleeding edge of research.
Previously Head of Applied Science at HomeX innovating in NLP, conversational AI, optimization and logistics for the home experience industry.
Senior Director at eBay building their product knowledge graph. Panelist at ISWC and co-author on Industrial-Scale Knowledge Graphs.
Ex-Googler where I worked on Fraud detection and ML Platforms. Taught Google’s machine learning crash course to google engineers and campus startups.
Worked across several industries including healthcare, industrial monitoring, semantic technologies, AI, advertising, online-retail and home services. All with the common goal of building solutions to complex problems in a simple and intelligent way.
Successful exits in machine learning startups:
- Fraud detection in display-advertising using ML at scale - acquired by Google
- AI Question Answering service - acquired by Amazon, turned into Alexa
- Healthcare and industrial monitoring with machine learning - acquired by Rolls Royce
Technical Specialities:
- Applying state of the art ML to real world problems
- Vision, Language, Industrial and Biomedical signal processing
- Deep Learning, Probabilistic Methods, Kernel Methods, Clustering, Signal Processing
- Semantic Technologies, Knowledge Graphs, RDF/OWL and reasoning
- Software architecture, design and delivery