Nathan Benaich

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.