Artificial Intelligence

He noted that “AI algorithms in Moscow are used in healthcare, education, security, and smart city technology….and very soon the Government will have to adopt a digital transformation strategy…with practical measures to introduce AI algorithms. He noted that “AI algorithms in Moscow are used in healthcare, education, security, and smart city technology….and very soon the Government will have to adopt a digital transformation strategy…with practical measures to introduce AI algorithms. The Government discussed this issue at length and made an absolutely correct decision regarding two matters:” Contrast this policy with the US and UK tax policies that will likely only see hikes for businesses and entrepreneurs (take note!). Amongst them was SMIC, mainland China’s answer to TSMC, which said that their ban will badly affect the company’s R&D and production capacity as they move to the 10nm node.

The truth is somewhat in between: in the same way that deep learning crushing all other methods to solve ImageNet does not mean that computer vision is solved, AlphaFold 2 crushing all other entrants in CASP to max out the competition score does not mean that protein folding is solved. After a couple of quarters flashing an increasingly obvious “Add Google Meet video conferencing” on every new Google calendar entry while Zoom’s share price soared, Google is now ramping up its efforts to compete. Three of the hottest topics in the MLOps space, which concerns lifecycle management of ML systems in production, are 1) feature stores, 2) data catalogs, and 3) data quality monitoring. Third, data quality monitoring systems help data producers and consumers understand whether there are issues/anomalies with the data.

These include conflating the diagnostic task with the diagnostic algorithm, a superficial definition of the diagnostic task, difficulties in comparing similar algorithms, insufficient characterization of safety and performance elements, and a lack of resources to assess performance at each installed site. While some companies (e.g. Apple, MSFT) are taking more thoughtful approaches and new legal precedents are set in the UK, an investigation by Amnesty International revealed that three companies based in France, Sweden, and the Netherlands sold facial recognition technology to key players of the Chinese mass surveillance apparatus. Even though NVIDIA is adding sweeteners to the deal, e.g. building a £40M supercomputer for health AI research in Cambridge (UK), it appears that Chinese technology companies are pushing the state to block the deal unless access to Arm’s designs remains unhindered. Given Arm’s hundreds of licensees who depend on its RISC technology, there is concern that its ownership by NVIDIA could jeopardize unhindered technology access (not factoring the issues of geopolitics).

There’s something for everyone 😉 Open sourcing AI research is important for accountability, reproducibility and driving progress in AI but, in reality, the vast majority of AI research papers are behind corporate lock and key. A condition of publication in a Nature Research journal is that authors are required to make materials, data, code, and associated protocols promptly available to readers without undue qualifications. There is huge amount of value-add innovation driven by startups that operate around the periphery of the compute-intensive R&D work conducted by big tech and others who believe in the scaling hypothesis (more progress requires more compute). Startups trade research for engineering by focusing on adapting novel architecture ideas with task or domain-specific insights to yield robust solutions that work in the real world.

The writer is a biologist, general partner of Air Street Capital and co-author of State of AI Report In late February, an artificial intelligence algorithm created by MIT researchers made front-page news for discovering a powerful new antibiotic that could save millions of lives by treating drug-resistant diseases. A company called C3.ai compiled data sets for AI researchers to crunch. The AI-first drug discovery company Recursion released a morphological image data set of Covid-19 infected cells as they react to thousands of drugs.

Novartis came in first with 20 internal AI projects and 8 cooperations with startups (AstraZeneca came in #2), while Gilead came in last with 1 internal AI project and 1 startup collaboration. A study of scientific publications, patents, company reports for 21 major pharmaceutical companies between 2014 and 2019 concluded that the industry is in an “early mature” phase of using AI in their businesses. Novartis came in first with 20 internal AI projects and 8 cooperations with startups (AstraZeneca came in #2), while Gilead came in last with 1 internal AI project and 1 startup collaboration. The big news in chip land is the rumored acquisition of ARM by NVIDIA for over $32B. ARM has struggled to grow under SoftBank’s ownership despite throwing profitability out the window.

I am very pleased to announce the speakers for the next Live edition of THE AI FUTURE SHOW Jen Stirrup will be joining me to discuss all things AI Delivery Challenges Nigel is Director of the Founder and CEO of Data Relish We will be focused on the topic of AI Delivery Challenges & Opportunities Join via Live Streaming, reserve your ticket to get details of the live channels here In parallel to the monthly live talk shows, THE AI FUTURE SHOW is also available as a Podcast, so feel free to listen to previous shows.

I am very pleased to announce the speakers for the next Live edition of THE AI FUTURE SHOW Nigel Crook will be joining me to discuss all things AI Ethics Nigel is Director of the Institute for Ethical AI at Oxford Brookes University. We will be focused on the topic of AI Ethics Join via Live Streaming, reserve your ticket to get details of the live channels here In parallel to the monthly live talk shows, THE AI FUTURE SHOW is also available as a Podcast, so feel free to listen to previous shows.

Part of the reason we don’t see more AI in genomic medicine is the issue of limited access to quality datasets (an issue that Pearse Keane discussed at our RAAIS conference last week), imbalanced datasets that result in algorithmic bias, and immature technology infrastructure to facilitate the adoption of predictive systems in healthcare. LabGenius (an Air Street Capital portfolio company) shared their 8-step approach to AI-first protein engineering applied to therapeutic discovery and development. Following the release of their 175 billion parameter GPT-3 language model, OpenAI announced they have developed an API for third party developers to access new models developed by the company. Although the best model submission achieved 82.56% average precision on the public dataset, the same model dropped to 65.18% average precision against the black box dataset.

I am very pleased to announce the speakers for the first Live version of THE AI FUTURE SHOW Stuart Sherman and Barry Singleton from Scaled Insights will be joining me to discuss some of the great work they are doing in the field of Artificial Intelligence to deliver value and innovation to their clients. We will be discussing the latest developments of intelligent technologies that are empowering digital transformation and giving businesses sustained competitive advantage. I am sure we will also talk about on the cutting edge area of Behavioural AI Join either via Zoom (and be able to ask questions) or Live Streaming, reserve your ticket for either here – https://the-ai-future-show.eventbrite.com In parallel to the monthly live talk shows, THE AI FUTURE SHOW will also be available as a Podcast (launching later this month).