Lifeboat Foundation

The picture was the result of the first six months of operation of eROSITA (Extended Roentgen Survey with an Imaging Telescope Array), one of two X-ray telescopes that were launched into space in July 2019 aboard the Russian spacecraft SRG (Spectrum-Roentgen-Gamma). eROSITA scans the sky as the spacecraft spins, and collects data over wider angles than are possible for most other X-ray observatories. This enables it to slowly sweep the entire sky every six months.

By an unusual arrangement, the eROSITA team is split into two — with a group based in Germany and one based in Russia — and each has exclusive access to eROSITA data from only half of the sky. The mission was originally intended to cover the sky eight times. But Russia’s full-scale invasion of Ukraine in 2022 led the German government to freeze its collaborations, and eROSITA was put on stand-by. By then, it had completed four full sky scans.

The data that Bulbul and her collaborators have used so far were from their half of the sky, collected during the first scan. Even so, the results are already among the most precise cosmological measurements ever made. It is unclear when the Russia-based group will publish its data and analysis.

Earlier this week I went to a roundtable in London hosted by the UK government’s Office for Quantum to gather views from industry and academia about adapting the UK workforce to quantum technologies. The Quantum Skills Taskforce Workshop was co-hosted with techUK, a UK-based trade organization for the technology sector. Featuring 60 participants from academia and industry, the day featured lively discussion and debate about what the next decade has in store for the UK quantum sector.

All major economies around the world now seem to have their own quantum plan and the UK is no exception. In fact, the UK is onto its second National Quantum Strategy, which was launched in March 2023 by the Department for Science, Innovation and Technology (DSIT). Setting goals for the UK to become a “quantum-enabled economy” by 2033, it also established an Office for Quantum within the DSIT.

He added, however, that “the technology is moving fast as well”. He said the institute should put in place standards that other governments and companies can follow, such as “red teaming”, where specialists simulate misuse of an AI model, rather than take on all the work itself.

Warner said the government could find itself in a situation where it was “red teaming everything” and that a backlog could build up “where they don’t have the bandwidth to get to all the models fast enough”

Referring to the institute’s potential as an international standard setter, he said: “They can set really brilliant standards such that other governments, other companies … can red team to those standards. So it’s a much more scalable, long-term vision for how to keep these things safe.”

Altman estimates that he would need between $5 trillion and $7 trillion to overhaul the semiconductor industry, which is currently dominated by Nvidia, the leading provider of graphics processing units (GPUs) for AI applications. Nvidia’s market cap has soared to $1.72 trillion in 2023, surpassing many tech giants such as Amazon and Alphabet. Altman wants to challenge Nvidia’s monopoly and create more competition and innovation in the AI chip market.

White House’s $11 billion bet on US semiconductor

Meanwhile, The White House announced the US government’s plan to spend $11 billion on semiconductor-related research and development on Friday. This move comes in the wake of Congress approving the Chips and Science Act in August 2022, which provides $52.7 billion for semiconductor production and R&D. Of this, $39 billion is allocated for subsidies and $11 billion for R&D.

Sam Altman was already trying to lead the development of human-level artificial intelligence. Now he has another great ambition: raising trillions of dollars to reshape the global semiconductor industry.

The OpenAI chief executive officer is in talks with investors including the United Arab Emirates government to raise funds for a wildly ambitious tech initiative that would boost the world’s chip-building capacity, expand its ability to power AI, among other things, and cost several trillion dollars, according to people familiar with the matter. The project could require raising as much as $5 trillion to $7 trillion, one of the people said.

The fundraising plans, which face significant obstacles, are aimed at solving constraints to OpenAI’s growth, including the scarcity of the pricey AI chips required to train large language models behind AI systems such as ChatGPT. Altman has often complained that there aren’t enough of these kinds of chips—known as graphics processing units, or GPUs—to power OpenAI’s quest for artificial general intelligence, which it defines as systems that are broadly smarter than humans.

By connecting several less-advanced chips into one, Chinese companies could circumvent the sanctions set by the US government.

I’m excited to share my latest Opinion article on AI at The Hill, a top political site/paper read by the White House and Congress:

Regardless what politicians promise, this age of AI and robots will also affect the size and growth rates of the U.S. government. Federal and state government may not immediately take up with automation and AI to the extent the private sector does, but eventually the stark rationality of lower overhead expenses—and thus lower taxes for citizens—will prevail.

This is a good thing. A smaller, nimble, more efficient government will benefit the majority of people.

Continue reading “AI can stop government from growing, and that’s a good thing” »

The Telangana state government in South India, in collaboration with various agricultural aid organizations and technology companies, launched a groundbreaking project known as “Saagu Baagu.” This initiative focused on assisting 7,000 chilli farmers with AI-powered tools, marking a significant step…

Saagu Baagu shows AI’s growing role in agriculture, helping developing-world farmers achieve sustainable and profitable practices.

Abstract. Important progress has been made over the last decade in the classification, imaging, and treatment of neuroendocrine neoplasm (NENs), with several new agents approved for use. Although the treatment options available for patients with well-differentiated neuroendocrine tumors (NETs) have greatly expanded, the rapidly changing landscape has presented several unanswered questions about how best to optimize, sequence, and individualize therapy. Perhaps the most important development over the last decade has been the approval of ¹⁷⁷ Lu-DOTATATE for treatment of gastroenteropancreatic-NETs, raising questions around optimal sequencing of peptide receptor radionuclide therapy (PRRT) relative to other therapeutic options, the role of re-treatment with PRRT, and whether PRRT can be further optimized through use of dosimetry among other approaches. The NET Task Force of the National Cancer Institute GI Steering Committee convened a clinical trial planning meeting in 2021 with multidisciplinary experts from academia, the federal government, industry, and patient advocates to develop NET clinical trials in the era of PRRT. Key clinical trial recommendations for development included 1) PRRT re-treatment, 2) PRRT and immunotherapy combinations, 3) PRRT and DNA damage repair inhibitor combinations, 4) treatment for liver-dominant disease, 5) treatment for PRRT-resistant disease, and 6) dosimetry-modified PRRT.