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How AI leaders want to outflank China

Protocol Enterprise

Hello and welcome to Protocol Enterprise! Today: how the U.S. and Singapore are developing AI policy with China in mind, Google builds a house by the lake, and Boeing bolsters its multicloud plans.

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The White House reaffirmed its mission to increase AI collaboration between the U.S. and Singapore last week. But during those talks, another country was on everyone’s minds: China.

When President Joe Biden hosted Singapore Prime Minister Lee Hsien Loong on March 29, he acknowledged the bilateral strategic partnership between the two nations — and the 5,400 U.S. companies with locations in Singapore. On the sidelines, U.S. Commerce Department representatives met with Singapore officials to expand the countries’ economic efforts related to trustworthy AI, data privacy, digital trade standards and advanced manufacturing.

  • Those efforts build on a previous Memorandum of Understanding, called the U.S.-Singapore Partnership for Growth and Innovation, the two countries signed in October.
  • Alex Capri, a researcher and consultant studying trade flows and competition in tech innovation who has taught at the National University of Singapore Business School, said the expanded plan is part of a much broader U.S. strategy aimed at China.
  • The partnership is designed to rebalance and re-engage Asian countries including smaller tech powers such as Singapore — “absolutely with the intention of reducing reliance on China for AI development, and also because of the strategic implications,” Capri said. “Singapore is a logical choice as a tech hub.”

The drumbeat in the U.S. to slow China’s mission to dominate AI is growing stronger.

  • Not only are tech industry leaders such as former Google CEO and AI investor Eric Schmidt turning up the anti-China volume in political and defense circles, but also legislators have asked the Commerce Department to further restrict export of AI and other U.S. technologies to companies with connections to China’s military.
  • One key focus of the expanded U.S.-Singapore pact is a plan to develop ethical AI governance approaches that facilitate interoperable cross-border connections.
  • “One practical example of our digital cooperation is on aligning our respective AI governance frameworks,” said Josephine Teo, Singapore’s minister for Communications and Information. “Companies can expect to deploy AI across borders with greater ease, to seize innovation opportunities while managing the risks.”

In their agreement to expand their partnership, the U.S. and Singapore also announced plans for more collaboration on tech standards and advanced manufacturing. These efforts reflect both nations’ goals to foster data and tech interoperability and connectivity related to digital trade, Capri said.

  • What all this means practically speaking, from either a geopolitical or a technical standpoint, is not yet clear.
  • But the general sentiment behind official statements reflecting last week’s meetings indicates the countries aim to streamline open data and technology supply chain flows.
  • “The United States and Singapore affirm the importance of ensuring that critical and emerging technologies foster an open, accessible, and secure technology ecosystem, based on mutual trust, confidence, and respect for a rules-based international order,” Biden and Hsien Loong said in a joint statement.
  • A Commerce Department spokesperson told Protocol the U.S. and Singapore will compare Singapore’s industry-aimed Minimum Viable Product for AI Governance Testing Framework with a risk management framework in development by the U.S. National Institute of Standards and Technology to determine how the two might align.

While the U.S. does not have any laws or blanket regulatory regime to address AI governance or related data use, Singapore created its Model AI Governance Framework for ethical AI approaches in 2019, which addresses explainability, fairness and the need for AI to be “human-centric.”

  • China itself has begun to implement its own rules restricting use of algorithmic recommendation systems.
  • However, the country’s efforts to develop — and in some ways, control — corporate AI and other emerging tech have people throughout Western governments concerned about its use of facial recognition, algorithmic social scoring, flagrant human rights abuses and the increased potential for AI-fueled military dominance.
  • Broadly speaking, by emphasizing collaborative AI governance and data frameworks, the U.S. and Singapore were speaking what Capri called “code language for the formation around ideological values.”

In essence, while China has established strict data controls requiring companies operating there to localize data and share data decryption keys, the U.S. and Singapore have reiterated their commitment to a more-open approach taken by liberal democracies when it comes to data use and tech interoperability.

  • In the U.S.-Singapore relationship, those sorts of controls would not apply, Capri said.

— Kate Kaye (email|twitter)


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A house by the lake

Google Cloud plans to launch a new data lake storage engine based on its popular BigQuery data warehouse to help remove barriers preventing customers from mining the full value of their ever-increasing data.

BigLake, now available in preview, allows enterprises to unify their data warehouses and data lakes to analyze data without worrying about the underlying storage format or systems, according to Sudhir Hasbe, Google Cloud’s senior director of Product Management for data analytics.

“The biggest advantage is then you don't have to duplicate your data across two different environments and create data silos,” Hasbe said in a press briefing prior to Wednesday’s Google Data Cloud Summit, where BigLake was announced.

With BigLake, Google Cloud is extending the capabilities of its 11-year-old BigQuery to data lakes on Google Cloud Storage to enable a flexible, open lakehouse architecture, according to the cloud provider. A data lakehouse is an open data-management architecture that combines data-warehouse-like data management and optimization functions, including business intelligence, machine learning and governance, for data lakes that typically provide more cost-effective storage.

“When you think about limitless data, it is time that we end the artificial separation between managed warehouses and data lakes,” said Gerrit Kazmaier, Google Cloud’s vice president and general manager for database, data analytics and Looker. “Google is doing this in a unique way.”

— Donna Goodison (email | twitter)

Cloud traffic control

While debate continues over whether or not it really makes sense to use multiple cloud infrastructure providers, Boeing is already at cruising altitude. The aircraft-maker announced Wednesday that it has signed new cloud deals that build on existing relationships with each member of the Big Three: AWS, Microsoft and Google.

But while Boeing picks and chooses what it needs from among the three major U.S. cloud providers, “most of Boeing’s applications now are hosted and maintained through on-site servers, managed by Boeing or external partners,” it said in its press release. That’s probably common among companies of Boeing’s age and size, and it means there’s likely a lot of runway ahead for each cloud provider to win new business.

— Tom Krazit (email | twitter)

Around the enterprise

Google launched a new alliance between several database and analytics companies including Databricks, Confluent and MongoDB to “make data more portable and accessible,” although without AWS, Microsoft and Snowflake this looks like another alliance disguised as a competitive marketing message.

Intel shut down all its operations in Russia weeks after cutting off shipments to the country in line with U.S. sanctions against chipmakers supplying the Russian economy.

The U.S. government said it removed malware on compromised networking devicesused by a botnet group operated by the Russian military to launch DDoS attacks against targets.

Security researchers discovered what is believed to be the first malware written specifically for AWS’ Lambda serverless computing service, designed for — what else, in 2022 — cryptocurrency mining.


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