SambaNova Systems Unveils Deep Learning Platform Purpose-Built for Financial Services Firms


Heavily funded and previously somewhat secretive artificial intelligence startup SambaNova Systems Inc. today announced what it says is the first AI platform purpose-built for the financial services industry.

The SambaNova GPT Banking service is designed to allow banks to start their AI capabilities in days or weeks at most.

With over $1 billion in funding behind it and a massive $5 billion valuation, SambaNova has designed and built an integrated hardware and software platform it claims can run AI and data applications. from the data center to the edge. Its DataScale hardware platform uses custom seven-nanometer chips that SambaNova says are more suited to machine learning and deep learning processes than the general-purpose microprocessors and graphics processing units widely used for such. tasks today.

The platform’s reconfigurable dataflow architecture runs an integrated open-source software stack called SambaFlow that allows each machine learning model to run optimally. It does this by minimizing the need to interface with memory, eliminating the main bottleneck of AI, which is the interconnect between chips and memory.

SambaNova GPT Banking is the first industry-specific offering to run on this stack. It is offered as a subscription service to help banks and other financial services firms deploy advanced machine learning models in a fraction of the time it would normally take, the company said.

SambaNova said there is a great need for such a solution, as many financial services firms struggle to deploy AI fast enough to meet their needs. SambaNova calls this the “deep learning deployment deficit,” explaining that it takes an average of 18 months for banks to hire a skilled data science team, build the infrastructure they need, and then train and deploy them. large language models. At that point, the models are already obsolete, as the size of the base model will have increased 10 times while the computational requirements will have increased significantly.

“We built GPT Banking to improve banks’ competitiveness and efficiency while accelerating their digital transformation,” said SambaNova co-founder and CEO Rodrigo Liang (pictured). “AI is the fastest and most cost effective tool to do this today and our service can be deployed and delivering value in weeks.”

SambaNova said GPT Banking has multiple uses, including sentiment analysis, scanning social media posts, traditional media and other sources to understand financial markets and investor sentiment. It can help with entity recognition, human error reduction, and document classification to reduce manual and repetitive work. It also performs language generation tasks such as processing, transcribing and prioritizing claims and requests, creating documents and extracting information from them, and translating documents into different languages.

“GPT Banking has the potential to transform nearly every aspect of banking, from improving operations to managing risk and compliance,” Liang added.

Analyst Andy Thurai of Constellation Research Inc. told SiliconANGLE that SambaNova’s GPT Banking model is based on Open AI LLC’s Generative Pre-trained Transformer 3. It is an auto-regressive language prediction model that uses deep learning to produce and analyze human-like text.

Thurai said that while GPT-3 has shown itself to be very capable in parsing text, it has many issues, including the fact that it was trained on publicly available text which likely has a lot of biases and is not cleaned properly. As a result, it can end up producing biased models that give biased results, he said.

“Text, thought processes, and assets from regulated industries such as finance and insurance never make it into the public domain, so models trained by OpenAI’s GPT-3 are not accurate when ‘It’s about industry-specific topics in regulated industries,’ he said. . “Given the ties between OpenAI and Microsoft Azure, it is conceivable that GPT-3 is not fully open but somewhat controlled by Microsoft interests.”

With that in mind, Thurai said, it’s great to see SambaNova bringing banking and finance-specific GPT to market.

“While all the associated work in areas of NLP such as sentiment analysis, entity recognition, language generation and language translation has already existed with vendors such as OpenAI and Google, this set of financial industry-specific solutions will hopefully add a layer of knowledge to the original GPT,” he said. “This used to be a huge limitation in regulated industries that were widely adopting AI.”

The launch of GPT Banking suggests that SambaNova is ready to start serving businesses on a much larger scale. Until now, he has always been very secretive about the companies using his platform, although it has previously been said that he works on projects related to the US Defense Advanced Research Projects Agency.

Photo: SambaNova Systems

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