healthcarereimagined

By ALEXANDRA KELLEYOCTOBER 28, 2024 03:27 PM ET

Following the release of the first set of post-quantum encryption algorithms, the National Institute of Standards and Technology is advancing a second series of options to protect important data.

The National Institute of Standards and Technology announced a new series of digital signature algorithms ready for the agency’s post-quantum cryptographic standardization process, following the finalization of the inaugural three earlier this year.

14 new algorithms are now candidates for PQC standardization after over a year of evaluation, the agency confirmed. These algorithms are intended to be implemented in networks prior to the advent of a potential fault-tolerant quantum computer.

The algorithms are designed to protect against that future quantum computer’s ability to process sufficiently large volumes of data and break the standard encryption schemes that protect today’s sensitive digital information. 

The algorithms’ names include CROSS, FAEST, HAWK, LESS, MAYO, Mirath, MQOM, PERK, QR-UOV, RYDE, SDitH, SNOVA, SQIsign, UOV. These candidates will now enter the second round for standardization, which the agency expects to take 12 to 18 months.

Article link: https://www.nextgov.com/emerging-tech/2024/10/nist-approves-14-new-quantum-encryption-algorithms-standardization/400608/

Pope Francis has made no secret of his intention to radically reform the administrative structures of the Catholic church, which he regards as insular, imperious, and bureaucratic. He understands that in a hyper-kinetic world, inward-looking and self-obsessed leaders are a liability.

Last year, just before Christmas, the Pope addressed the leaders of the Roman Curia — the Cardinals and other officials who are charged with running the church’s byzantine network of administrative bodies. The Pope’s message to his colleagues was blunt. Leaders are susceptible to an array of debilitating maladies, including arrogance, intolerance, myopia, and pettiness. When those diseases go untreated, the organization itself is enfeebled. To have a healthy church, we need healthy leaders.

Through the years, I’ve heard dozens of management experts enumerate the qualities of great leaders. Seldom, though, do they speak plainly about the “diseases” of leadership. The Pope is more forthright. He understands that as human beings we have certain proclivities — not all of them noble. Nevertheless, leaders should be held to a high standard, since their scope of influence makes their ailments particularly infectious.

The Catholic Church is a bureaucracy: a hierarchy populated by good-hearted, but less-than-perfect souls. In that sense, it’s not much different than your organization. That’s why the Pope’s counsel is relevant to leaders everywhere.

With that in mind, I spent a couple of hours translating the Pope’s address into something a little closer to corporate-speak. (I don’t know if there’s a prohibition on paraphrasing Papal pronouncements, but since I’m not Catholic, I’m willing to take the risk.)

Herewith, then, the Pope (more or less):

____________________

The leadership team is called constantly to improve and to grow in rapport and wisdom, in order to carry out fully its mission. And yet, like any body, like any human body, it is also exposed to diseases, malfunctioning, infirmity. Here I would like to mention some of these “[leadership] diseases.” They are diseases and temptations which can dangerously weaken the effectiveness of any organization.

1. The disease of thinking we are immortal, immune, or downright indispensable, [and therefore] neglecting the need for regular check-ups. A leadership team which is not self-critical, which does not keep up with things, which does not seek to be more fit, is a sick body. A simple visit to the cemetery might help us see the names of many people who thought they were immortal, immune, and indispensable! It is the disease of those who turn into lords and masters, who think of themselves as above others and not at their service. It is the pathology of power and comes from a superiority complex, from a narcissism which passionately gazes at its own image and does not see the face of others, especially the weakest and those most in need. The antidote to this plague is humility; to say heartily, “I am merely a servant. I have only done what was my duty.”
2. Another disease is excessive busyness. It is found in those who immerse themselves in work and inevitably neglect to “rest a while.” Neglecting needed rest leads to stress and agitation. A time of rest, for those who have completed their work, is necessary, obligatory and should be taken seriously: by spending time with one’s family and respecting holidays as moments for recharging.
3. Then there is the disease of mental and [emotional] “petrification.” It is found in leaders who have a heart of stone, the “stiff-necked;” in those who in the course of time lose their interior serenity, alertness and daring, and hide under a pile of papers, turning into paper pushers and not men and women of compassion. It is dangerous to lose the human sensitivity that enables us to weep with those who weep and to rejoice with those who rejoice! Because as time goes on, our hearts grow hard and become incapable of loving all those around us. Being a humane leader means having the sentiments of humility and unselfishness, of detachment and generosity.
4. The disease of excessive planning and of functionalism. When a leader plans everything down to the last detail and believes that with perfect planning things will fall into place, he or she becomes an accountant or an office manager. Things need to be prepared well, but without ever falling into the temptation of trying to eliminate spontaneity and serendipity, which is always more flexible than any human planning. We contract this disease because it is easy and comfortable to settle in our own sedentary and unchanging ways.
5. The disease of poor coordination. Once leaders lose a sense of community among themselves, the body loses its harmonious functioning and its equilibrium; it then becomes an orchestra that produces noise: its members do not work together and lose the spirit of camaraderie and teamwork. When the foot says to the arm: ‘I don’t need you,’ or the hand says to the head, ‘I’m in charge,’ they create discomfort and parochialism.
6. There is also a sort of “leadership Alzheimer’s disease.” It consists in losing the memory of those who nurtured, mentored and supported us in our own journeys. We see this in those who have lost the memory of their encounters with the great leaders who inspired them; in those who are completely caught up in the present moment, in their passions, whims and obsessions; in those who build walls and routines around themselves, and thus become more and more the slaves of idols carved by their own hands.
7. The disease of rivalry and vainglory. When appearances, our perks, and our titles become the primary object in life, we forget our fundamental duty as leaders—to “do nothing from selfishness or conceit but in humility count others better than ourselves.” [As leaders, we must] look not only to [our] own interests, but also to the interests of others.
8. The disease of existential schizophrenia. This is the disease of those who live a double life, the fruit of that hypocrisy typical of the mediocre and of a progressive emotional emptiness which no [accomplishment or] title can fill. It is a disease which often strikes those who are no longer directly in touch with customers and “ordinary” employees, and restrict themselves to bureaucratic matters, thus losing contact with reality, with concrete people.
9. The disease of gossiping, grumbling, and back-biting.This is a grave illness which begins simply, perhaps even in small talk, and takes over a person, making him become a “sower of weeds” and in many cases, a cold-blooded killer of the good name of colleagues. It is the disease of cowardly persons who lack the courage to speak out directly, but instead speak behind other people’s backs. Let us be on our guard against the terrorism of gossip!
10. The disease of idolizing superiors. This is the disease of those who court their superiors in the hope of gaining their favor. They are victims of careerism and opportunism; they honor persons [rather than the larger mission of the organization]. They think only of what they can get and not of what they should give; small-minded persons, unhappy and inspired only by their own lethal selfishness. Superiors themselves can be affected by this disease, when they try to obtain the submission, loyalty and psychological dependency of their subordinates, but the end result is unhealthy complicity.
11. The disease of indifference to others. This is where each leader thinks only of himself or herself, and loses the sincerity and warmth of [genuine] human relationships. This can happen in many ways: When the most knowledgeable person does not put that knowledge at the service of less knowledgeable colleagues, when you learn something and then keep it to yourself rather than sharing it in a helpful way with others; when out of jealousy or deceit you take joy in seeing others fall instead of helping them up and encouraging them.
12. The disease of a downcast face. You see this disease in those glum and dour persons who think that to be serious you have to put on a face of melancholy and severity, and treat others—especially those we consider our inferiors—with rigor, brusqueness and arrogance. In fact, a show of severity and sterile pessimism are frequently symptoms of fear and insecurity. A leader must make an effort to be courteous, serene, enthusiastic and joyful, a person who transmits joy everywhere he goes. A happy heart radiates an infectious joy: it is immediately evident! So a leader should never lose that joyful, humorous and even self-deprecating spirit which makes people amiable even in difficult situations. How beneficial is a good dose of humor! …
13. The disease of hoarding. This occurs when a leader tries to fill an existential void in his or her heart by accumulating material goods, not out of need but only in order to feel secure. The fact is that we are not able to bring material goods with us when we leave this life, since “the winding sheet does not have pockets” and all our treasures will never be able to fill that void; instead, they will only make it deeper and more demanding. Accumulating goods only burdens and inexorably slows down the journey!
14. The disease of closed circles, where belonging to a clique becomes more powerful than our shared identity. This disease too always begins with good intentions, but with the passing of time it enslaves its members and becomes a cancer which threatens the harmony of the organization and causes immense evil, especially to those we treat as outsiders. “Friendly fire” from our fellow soldiers, is the most insidious danger. It is the evil which strikes from within. As it says in the bible, “Every kingdom divided against itself is laid waste.”
15. Lastly: the disease of extravagance and self-exhibition. This happens when a leader turns his or her service into power, and uses that power for material gain, or to acquire even greater power. This is the disease of persons who insatiably try to accumulate power and to this end are ready to slander, defame and discredit others; who put themselves on display to show that they are more capable than others. This disease does great harm because it leads people to justify the use of any means whatsoever to attain their goal, often in the name of justice and transparency! Here I remember a leader who used to call journalists to tell and invent private and confidential matters involving his colleagues. The only thing he was concerned about was being able to see himself on the front page, since this made him feel powerful and glamorous, while causing great harm to others and to the organization.

Friends, these diseases are a danger for every leader and every organization, and they can strike at the individual and the community levels.

____________________

So, are you a healthy leader? Use the Pope’s inventory of leadership maladies to find out. Ask yourself, on a scale of 1 to 5, to what extent do I . . .

• Feel superior to those who work for me?
• Demonstrate an imbalance between work and other areas of life?
• Substitute formality for true human intimacy?
• Rely too much on plans and not enough on intuition and improvisation?
• Spend too little time breaking silos and building bridges?
• Fail to regularly acknowledge the debt I owe to my mentors and to others?
• Take too much satisfaction in my perks and privileges?
• Isolate myself from customers and first-level employees?
• Denigrate the motives and accomplishments of others?
• Exhibit or encourage undue deference and servility?
• Put my own success ahead of the success of others?
• Fail to cultivate a fun and joy-filled work environment?
• Exhibit selfishness when it comes to sharing rewards and praise?
• Encourage parochialism rather than community?
• Behave in ways that seem egocentric to those around me?

As in all health matters, it’s good to get a second or third opinion. Ask your colleagues to score you on the same fifteen items. Don’t be surprised if they say, “Gee boss, you’re not looking too good today.” Like a battery of medical tests, these questions can help you zero in on opportunities to prevent disease and improve your health. A Papal leadership assessment may seem like a bit of a stretch. But remember: the responsibilities you hold as a leader, and the influence you have over others’ lives, can be profound. Why not turn to the Pope — a spiritual leader of leaders — for wisdom and advice?

Gary Hamel is a visiting professor at London Business School and the founder of the Management Lab. He is a coauthor of Humanocracy: Creating Organizations as Amazing as the People Inside Them(Harvard Business Review Press, 2020).

Article link; https://hbr.org/2015/04/the-15-diseases-of-leadership-according-to-pope-francis

BY UNIVERSITY OF PITTSBURGH OCTOBER 26, 2024

Researchers have unveiled a new photonic in-memory computing method that promises to advance optical computing significantly.

This technology, using magneto-optical materials, achieves high-speed, low-energy, and durable memory solutions suitable for integration with existing computing technologies.

Photonic In-Memory Computing

For the first time, a global team of electrical engineers has developed a new method for photonic in-memory computing, bringing optical computing closer to becoming a reality.

The team includes researchers from the University of Pittsburgh Swanson School of Engineering, the University of California – Santa Barbara, the University of Cagliari, and the Tokyo Institute of Technology (now the Institute of Science Tokyo). Their results were published on October 23 in the journal Nature Photonics(“Integrated non-reciprocal magneto-optics with ultra-high endurance for photonic in-memory computing.”

This research was a collaborative effort led by Nathan Youngblood, assistant professor of electrical and computer engineering at Pitt, along with Paulo Pintus, formerly of UC Santa Barbara and now an assistant professor at the University of Cagliari, and Yuya Shoji, associate professor at the Institute of Science Tokyo.

Overcoming Optical Memory Limitations

Until now, researchers have been limited in developing photonic memory for AI processing – gaining one important attribute like speed while sacrificing another like energy usage. In the article, the international team demonstrates a unique solution that addresses current limitations of optical memory that have yet to combine non-volatility, multibit storage, high switching speed, low switching energy, and high endurance in a single platform.

“The materials we use in developing these cells have been available for decades. However, they have primarily been used for static optical applications, such as on-chip isolators rather than a platform for high-performance photonic memory,” Youngblood explained. “This discovery is a key enabling technology toward a faster, more efficient, and more scalable optical computing architecture that can be directly programmed with CMOS (complementary metal-oxide semiconductor) circuitry – which means it can be integrated into today’s computer technology.

“Additionally, our technology showed three orders of magnitude better endurance than other non-volatile approaches, with 2.4 billion switching cycles and nanosecond speeds.”

Introducing a Resonance-Based Architecture

The authors propose a resonance-based photonic architecture that leverages the non-reciprocal phase shift in magneto-optical materials to implement photonic in-memory computing.

A typical approach to photonic processing is to multiply a rapidly changing optical input vector with a matrix of fixed optical weights. However, encoding these weights on-chip using traditional methods and materials has proven challenging. By using magneto-optic memory cells comprised of heterogeneously integrated cerium-substituted yttrium iron garnet (Ce:YIG) on silicon micro-ring resonators, the cells cause light to propagate bidirectionally, like sprinters running opposite directions on a track.

Computing by Controlling the Speed of Light

“It’s like the wind is blowing against one sprinter while helping the other run faster,” explained Pintus, who led the experimental work at UC Santa Barbara. “By applying a magnetic field to the memory cells, we can control the speed of light differently depending on whether the light is flowing clockwise or counterclockwise around the ring resonator. This provides an additional level of control not possible in more conventional non-magnetic materials.”

Future Prospects and Scaling

The team is now working to scale up from a single memory cell to a large-scale memory array which can support even more data for computing applications. They note in the article that the non-reciprocal magneto-optic memory cell offers an efficient non-volatile storage solution that could provide unlimited read/write endurance at sub-nanosecond programming speeds.

“We also believe that future advances of this technology could use different effects to improve the switching efficiency,” Shoji at Tokyo added, “and that new fabrication techniques with materials other than Ce:YIG and more precise deposition can further advance the potential of non-reciprocal optical computing.”

Reference: “Integrated non-reciprocal magneto-optics with ultra-high endurance for photonic in-memory computing” by Paolo Pintus, Mario Dumont, Vivswan Shah, Toshiya Murai, Yuya Shoji, Duanni Huang, Galan Moody, John E. Bowers and Nathan Youngblood, 23 October 2024, Nature Photonics.
DOI: 10.1038/s41566-024-01549-1

Other researchers on this project include:

• John E. Bowers, distinguished faculty at University of California at Santa Barbara
• Mario Dumont, graduate student researcher at University of California at Santa Barbara
• Duanni Huang, former researcher at University of California at Santa Barbara
• Galan Moody, faculty at University of California at Santa Barbara
• Toshiya Murai, researcher at National Institute of Advanced Industrial Science and Technology, Japan
• Vivswan Shah, graduate student researcher at University of Pittsburgh

Article link: https://scitechdaily.com/light-speed-breakthrough-the-dawn-of-photonic-in-memory-computing/

It’s still early days for our understanding of AI, so expect more glitches and fails as it becomes a part of real-world products.

By Melissa Heikkilä

March 5, 2024

This story originally appeared in The Algorithm, our weekly newsletter on AI. To get stories like this in your inbox first, sign up here.

I’ve been experimenting with using AI assistants in my day-to-day work. The biggest obstacle to their being useful is they often get things blatantly wrong. In one case, I used an AI transcription platform while interviewing someone about a physical disability, only for the AI summary to insist the conversation was about autism. It’s an example of AI’s “hallucination” problem, where large language models simply make things up. 

Recently we’ve seen some AI failures on a far bigger scale. In the latest (hilarious) gaffe, Google’s Gemini refused to generate images of white people, especially white men. Instead, users were able to generate images of Black popes and female Nazi soldiers. Google had been trying to get the outputs of its model to be less biased, but this backfired, and the tech company soon found itself in the middle of the US culture wars, with conservative critics and Elon Musk accusing it of having a “woke” bias and not representing history accurately. Google apologized and paused the feature. 

In another now-famous incident, Microsoft’s Bing chat told a New York Times reporter to leave his wife. And customer service chatbots keep getting their companies in all sorts of trouble. For example, Air Canada was recently forced to give a customer a refund in compliance with a policy its customer service chatbot had made up. The list goes on. 

Tech companies are rushing AI-powered products to launch, despite extensive evidence that they are hard to control and often behave in unpredictable ways. This weird behavior happens because nobody knows exactly how—or why—deep learning, the fundamental technology behind today’s AI boom, works. It’s one of the biggest puzzles in AI. My colleague Will Douglas Heaven just published a piece where he dives into it. 

The biggest mystery is how large language models such as Gemini and OpenAI’s GPT-4 can learn to do something they were not taught to do. You can train a language model on math problems in English and then show it French literature, and from that, it can learn to solve math problems in French. These abilities fly in the face of classical statistics, which provide our best set of explanations for how predictive models should behave, Will writes. Read more here. 

It’s easy to mistake perceptions stemming from our ignorance for magic. Even the name of the technology, artificial intelligence, is tragically misleading. Language models appear smart because they generate humanlike prose by predicting the next word in a sentence. The technology is not truly intelligent, and calling it that subtly shifts our expectations so we treat the technology as more capable than it really is. 

Don’t fall into the tech sector’s marketing trap by believing that these models are omniscient or factual, or even near ready for the jobs we are expecting them to do. Because of their unpredictability, out-of-control biases, security vulnerabilities, and propensity to make things up, their usefulness is extremely limited. They can help humans brainstorm, and they can entertain us. But, knowing how glitchy and prone to failure these models are, it’s probably not a good idea to trust them with your credit card details, your sensitive information, or any critical use cases.

As the scientists in Will’s piece say, it’s still early days in the field of AI research. According to Boaz Barak, a computer scientist at Harvard University who is currently on secondment to OpenAI’s superalignment team, many people in the field compare it to physics at the beginning of the 20th century, when Einstein came up with the theory of relativity. 

The focus of the field today is how the models produce the things they do, but more research is needed into why they do so. Until we gain a better understanding of AI’s insides, expect more weird mistakes and a whole lot of hype that the technology will inevitably fail to live up to. 

Deeper Learning

Google DeepMind’s new generative model makes Super Mario–like games from scratch

OpenAI’s recent reveal of its stunning generative model Sora pushed the envelope of what’s possible with text-to-video. Now Google DeepMind brings us text-to-video games. The new model, called Genie, can take a short description, a hand-drawn sketch, or a photo and turn it into a playable video game in the style of classic 2D platformers like Super Mario Bros. But don’t expect anything fast-paced. The games run at one frame per second, versus the typical 30 to 60 frames per second of most modern games.

Level up: Google DeepMind’s researchers are interested in more than just game generation. The team behind Genie works on open-ended learning, where AI-controlled bots are dropped into a virtual environment and left to solve various tasks by trial and error. It’s a technique that could have the added benefit of advancing the field of robotics. Read more from Will Douglas Heaven.

Bits and Bytes

What Luddites can teach us about resisting an automated future
This comic is a nice look at the history of workers’ efforts to preserve their rights in the face of new technologies, and draws parallels to today’s struggle between artists and AI companies. (MIT Technology Review) 

Elon Musk is suing OpenAI and Sam Altman
Get the popcorn out. Musk, who helped found OpenAI, argues that the company’s leadership has transformed it from a nonprofit that is developing open-source AI for the public good into a for-profit subsidiary of Microsoft. (The Wall Street Journal) 

Generative AI might bend copyright law past the breaking point
Copyright law exists to foster a creative culture that compensates people for their creative contributions. The legal battle between artists and AI companies is likely to test the notion of what constitutes “fair use.” (The Atlantic) 

Tumblr and WordPress have struck deals to sell user data to train AI 
Reddit is not the only platform seeking to capitalize on today’s AI boom. Internal documents reveal that Tumblr and WordPress are working with Midjourney and OpenAI to offer user-created content as AI training data. The documents reveal that the data set Tumblr was trying to sell included content that should not have been there, such as private messages. (404 Media) 

A Pornhub chatbot stopped millions from searching for child abuse videos
Over the last two years, an AI chatbot has directed people searching for child sexual abuse material on Pornhub in the UK to seek help. This happened over 4.4 million times, which is a pretty shocking number. (Wired) 

The perils of AI-generated advertising. Case: Willy Wonka
An events company in Glasgow, Scotland, used an AI image generator to attract customers to “Willy’s Chocolate Experience,” where “chocolate dreams become reality”—only for customers to arrive at a half-deserted warehouse with a sad Oompa Loompa and depressing decorations. The police were called, the event went viral, and the internet has been having a field day since. (BBC) 

Article link: https://www-technologyreview-com.cdn.ampproject.org/c/s/www.technologyreview.com/2024/03/05/1089449/nobody-knows-how-ai-works/amp/

As national labs invest in next-generation AI research, David Turk explains how the government fits into the AI age. 

BYREBECCA HEILWEIL

OCTOBER 8, 2024

The Energy Department could be a key force in counteracting the “profit motive” driving America’s leading artificial intelligence companies, the agency’s second-in-command said in an interview. 

DOE Deputy Secretary David Turk told FedScoop that top AI firms aren’t motivated to pursue all the use cases most likely to benefit the public, leaving the U.S. government — which maintains a powerful network of national labs now developing artificial intelligence infrastructure of their own — to play an especially critical role.

Turk’s comments come as the Energy Department pushes forward with a series of AI initiatives. One key program is the Frontiers in Artificial Intelligence for Science, Security, and Technology, or FASST effort, which is meant to advance the use of powerful datasets maintained by the agency in order to develop science-forward AI models. At Lawrence Livermore National Laboratory in California, federal researchers are working on building the world’s fastest supercomputer, El Capitan. The current fastest, Frontier, is based at the Oak Ridge National Laboratory in Tennessee, which also falls under the auspices of the federal government.

Through the Energy Department’s data and research staff, Turk says the agency is hoping to focus on areas of AI the private sector isn’t motivated to seek out — while also countering some of the negative consequences spurred by the race to build the technology. 

“These [companies] are shareholder-driven and they’re looking to turn a profit. But not everything that is valuable to society as a whole has a huge amount of profit behind it, especially in the near term and in the way that we’ve seen history play out,” Turk said. “It is going to take the government, without the full profit motive and without the intense competition of the private sector, to say, hold on, let’s kick the tires. Let’s make sure we’re doing this right.” 

That’s not to say the Energy Department or the national laboratories have a problem working with Big Tech. At the Pacific Northwest National Laboratory in Washington, there’s already plenty of work being done with ChatGPT, as well as with Microsoft, on battery chemistry research. OpenAI is working with the Los Alamos National Laboratory on bioscience research, too. 

As policymakers wrestle with how to prioritize U.S. competitiveness in artificial intelligence  while also curbing some of the worst impacts of the emerging technology — including data security risks, environmental costs, and potential bias — Turk spoke to FedScoop about how the government will try to position itself in the age of AI.

This interview has been edited for clarity and length. 

FedScoop: What is the Department of Energy’s role in this moment of AI? Everyone just watched “Oppenheimer” and has more familiarity with the history of the national labs.

Deputy Secretary David Turk:What’s striking to me is not just the nuclear security [or] Oppenheimer side of the house, which does a lot of AI and supercomputing, but also our Office of Science, where we have an $9 billion annual budget for science. Some of those laboratories have been at the very cutting edge on AI, supercomputing, quantum computing, and have huge, huge datasets that are incredibly helpful as well. For me, the foundation of our AI at the Department of Energy is not as appreciated as it should be. … It’s the supercomputer power, it’s the data, which is the fuel for AI, and then, maybe even most importantly, it’s the people. We’ve got such phenomenal talent, mostly in our national laboratories and some at our federal headquarters. 

FS: A lot of these companies are finding that there’s a ceiling in terms of what you can scrape from the public web, and a lot of the more specific applications of AI rely on more specific data, potentially data with higher security needs. How are you thinking about access to data that the Department of Energy might have? 

DT:If you don’t have good data, you’re not going to have good outputs, no matter how good your AI is. We have just phenomenal datasets that no one else has, including and especially from our national laboratories, who’ve been doing fundamental science, have been doing applied research, and have been really pushing the boundaries in any number of different areas.

… We do have a responsibility to do even more, [including] making sure that we’ve got the funding to be able to put that data out there, where it’s appropriate for public use and where it’s appropriate more for specialized use when we have some security issues. … Part of the FASST proposal is making that data more available for researchers where it’s appropriate to do so, and for others as well in more specialized areas. That’s a big part of our strategy. 

FS: There’s a lot of conversation about building a national AI capability. I’m curious how you would explain that to a member of the public. Is that something like a government version of GPT? Is this a science version of GPT, an LLM?

DT: I don’t think there’s going to be one AI to serve all purposes, right? There may be more generalized ChatGPT-like services, but then there’s going to be AI really trained on from the data perspective, from the algorithm perspective — on physics problems or bio problems or other kinds of science problems. 

The private sector is going to do what the private sector does and they have a profit motive in mind. That’s not to say that there aren’t good people working in companies, but these are companies, and these [companies] are shareholder-driven and they’re looking to turn a profit. But not everything that is valuable to society as a whole has a huge amount of profit behind it, especially in the near term and in the way that we’ve seen history play out. 

And so if we want to have AI benefiting the public as a whole, including use cases that don’t have that profit loaded squarely in the equation, then we need to invest in that and we need to have a place within our government, the Department of Energy, working with other partners to make sure we’re taking advantage of those more public-minded use cases going forward. 

Because these are profit-driven companies with intense competition among themselves, we need to have democratically elected government with real expertise and we need to hire up and make sure that we’ve got cutting-edge AI talent in our government to be able to do the red-teaming. [They need] to be able to research, for example, whether a model may get into areas that are really challenging, that a terrorist could use it to build a chem or bio weapon in a way that’s not good for anybody.’

We need to have that expertise within the U.S. government. We need to do the red-teaming and we need to have the regulations in place. All of that depends on having the human capability, the human talent, but also the datasets and the algorithms and other kinds of things that are necessary for the government to play its role on the offense side and the defense side.

FS: I got the chance to see Frontier maybe about a year ago, and that was super interesting. I’m curious, do we have enough supercomputers to meet the DOE goals on AI right now?

DT: We do have many of the world’s fastest supercomputers right now, and there’s others in the pipeline that will become the world’s fastest going forward. We need to keep investing. The short answer is, if we want to keep being on the cutting edge, we need to keep that level of investment. We need to keep pushing the boundaries. And we need to make sure that the U.S. government has capabilities, including on the compute power side of things. 

So we need to work with those partners in the private sector and keep pushing the envelope on the compute power, as well. I feel like we’re in a very strong place there. But again, with not only what’s going on in the private sector, but what’s going on in China and other countries, who also want to be the leaders in AI, we’ve got to keep investing, and we’ve got to compete — and we’ve got to out-compete from the U.S. government side of things, too. 

FS: I understand that the national labs do have some responsibility not just developing AI, but also analyzing potential risks that might come from private-sector models. Curious if you could summarize what you’re finding in terms of the biggest risks or biggest concerns with powerful AI models right now?

DT: This is a huge, huge responsibility and we need to invest in this side as well. We’ve got great capabilities. We’ve got great human talent. But if we’re going to keep tabs on what’s happening in the private sector — if we’re going to be able to do the red-teaming and other kinds of things that are necessary to make sure that these AI models are safe going forward — [we should do that] before they’re released more broadly, right? You don’t want the Pandora’s box to open. 

What’s clear to me in all our discussions internally in the U.S. government is we’ve got a lot of that expertise. So we’re not only doing it ourselves, but with some key partners. We’ve got relationships with Anthropic and many other AI companies on that front. We’re working hand in hand with others, including, especially, the Commerce Department. The Commerce Department is setting up this AI Safety Institute. We’re partnering with them so that we can take advantage of this expertise, this knowledge, this ability to work in the classified space — of course, working with our intel colleagues and our Department of Defense colleagues as well — and making sure that we all have an across-the-government effort to do all this more defensive work.

That’s something that’s in the interest of companies, but it is going to take the government, without the full profit motive and without the intense competition of the private sector, to say, hold on, let’s kick the tires. Let’s make sure we’re doing this right. Let’s make sure we don’t have any unintended consequences here. And this is going to be only even more important with each successive generation of AI, which gets more and more sophisticated, more and more powerful. 

This is why we put together this FASST proposal, why we’re having conversations with Congress about making sure that we have the funding to keep up the talent, keep up the compute power, keep up the ability of the algorithms to make sure that we’re playing this incredibly important role.

Written by Rebecca Heilweil

Rebecca Heilweil is an investigative reporter for FedScoop. She writes about the intersection of government, tech policy, and emerging technologies. Previously she was a reporter at Vox’s tech site, Recode. She’s also written for Slate, Wired, the Wall Street Journal, and other publications. You can reach her at rebecca.heilweil@fedscoop.com. Message her if you’d like to chat on Signal.

Article link: https://fedscoop.com/deputy-energy-secretary-ai-industry-profit-motive/?

by Beth Stackpole

Aug 6, 2024

Why It Matters

Generative artificial intelligence will affect economic growth more quickly than other general-purpose technologies, according to a new report. Share 

The steam engine, the internal combustion engine, electrification, and computers are all considered “general-purpose technologies” — new tools that are powerful enough to accelerate overall economic growth and transform economies and societies. According to many experts, generative artificial intelligence will be the next invention to join that category.

In a recent report about the economic impact of generative AI, Google visiting fellow and MIT Sloan principal research scientist Andrew McAfee makes the case that generative AI is not only a game-changing general-purpose technology but could also spur change far more quickly than preceding innovations due to its accessibility and ease of diffusion. 

General-purpose technologies possess three key characteristics that ensure that they will have a large and positive economy-wide impact on productivity and growth. Though generative AI is still relatively new, McAfee writes that generative AI has these characteristics: 

Rapid improvement. Though it became mainstream only a few years ago, generative AI has quickly improved at generating relevant and accurate content in response to user prompts. McAfee notes that OpenAI’s GPT 3.5 system, released in late 2022, performed better on the U.S. bar exam than about 10% of the human test-takers. GPT 4, released in March 2023, performed better than 90% of those taking the bar exam. 

Generative AI’s “context window” — how much information it can accept from users — has also grown quickly. In 2020, state-of-the-art generative AI systems could accommodate approximately seven and a half pages of text; in late 2023, that window was 40 times larger, up to nearly 300 pages of text.

Pervasiveness. General-purpose technologies need to be widely implemented — which is already true of generative AI. In a 2023 survey of 14,000 users across a range of industries and professions, 28% of respondents said that they are using generative AI at work — over half without formal approval from their employer — and another 32% expected to use the technology at work soon. Another 2023 study found that about 80% of U.S. workers could have at least 10% of their work tasks affected by the introduction of generative AI. About 19% of workers could see at least half of their work tasks affected by the technology, the study found. 

Complementary innovations. While generative AI can quickly generate text, pictures, and sound from prompts, there is plenty of work being done to push it beyond those boundaries. Generative AI is being used not just to improve individual tasks but to streamline entire processes, McAfee writes, and researchers are confident that innovations making use of generative AI’s capabilities will advance science and engineering. 

“Because of generative AI’s rapid improvement, pervasiveness, and clear potential for complementary innovation, we are confident that it merits the label of ‘general-purpose technology,’” McAfee writes.

Generative AI’s accelerated pace of change  

Past general-purpose technologies took time to have a transformational impact, mainly because they required a new infrastructure. For example, electrical transmission networks needed to be in place to take advantage of electrification. In addition, most advantages associated with past technologies materialized only after users had had the chance to ideate and implement complementary innovations, McAfee writes.

RELATED ARTICLES

How generative AI can boost highly skilled workers’ productivityFrom MIT, a technically informed approach to governing AIHere comes the AI productivity boom

In contrast, generative AI’s effects will manifest more quickly because much of the required infrastructure — internet-connected devices — is immediately available and already widely used. Generative AI doesn’t require mastery of computer skills or proficiency in a programming language, as people use natural human language to interact with the system.

In terms of being an engine for economic growth, experts predict serious gains. Goldman Sachs estimates that generative AI will be responsible for a 0.4 percentage point increase in GDP growth in the United States over the next decade. There are also ramifications beyond growth statistics. By automating mundane tasks, generative AI will allow people to do more meaningful work, whether that’s enabling physicians to spend less time on paperwork and more time caring for patients or helping professionals dig into upskilling and training.

However, there are also concerns that people across industries will need to learn new skills and rethink their career paths. There are risks associated with disinformation as well.

Despite these drawbacks, McAfee writes that generative AI has the potential to fuel wide-scale economic growth. 

“Generative AI is already improving the productivity and quality of many tasks, and the technology is beginning to be used to redesign multi-step, multi-group processes, making them faster and less labor-intensive,” McAfee writes. “This technology’s deepest impact on the world of work will come as it’s used to reimagine entire organizations. This deep reimagination will be a decentralized and distributed phenomenon, carried out by innovators and entrepreneurs throughout the economy.”

Article link: https://mitsloan.mit.edu/ideas-made-to-matter/impact-generative-ai-a-general-purpose-technology?

Computers capable of crunching a quintillion operations per second are expanding the limits of what scientists can simulate.

By Sophia Chenarchive page

January 8, 2024

WHO

Oak Ridge National Lab, Jülich Super­computing Centre, China’s Supercomputing Center in Wuxi

WHEN

Now

In May 2022, the global supercomputer rankings were shaken up by the launch of Frontier. Now the fastest supercomputer in the world, it can perform more than 1 quintillion (10¹⁸) floating-point operations per second. That’s a 1 followed by 18 zeros, also known as an exaflop. Essentially, Frontier can perform as many calculations in one second as 100,000 laptops.

With the launch of Frontier, located at Oak Ridge National Laboratory in Tennessee, the era of exascale computing officially began. Several more such exascale computers will soon join its ranks. In the US, researchers are installing two machines that will be about twice as fast as Frontier: El Capitan, at Lawrence Livermore National Laboratory in California, and Aurora, at Argonne National Laboratory in Illinois. Europe’s first exascale supercomputer, Jupiter, is expected to come online in late 2024. China reportedly also has exascale machines, although it has not released results from standard benchmark tests.

Related Story

What’s next for the world’s fastest supercomputers

Scientists have begun running experiments on Frontier, the world’s first official exascale machine, while facilities worldwide build other machines to join the ranks.

Scientists and engineers are eager to use these turbocharged computers to advance a range of fields. Astrophysicists are already using Frontier to model the flow of gas in and out of the Milky Way; in addition to simulating motion on the scale of our galaxy, their model can zero in on exploding stars. This application showcases supercomputers’ unique ability to simulate physical objects at multiple scales simultaneously. 

The progress won’t stop here. For the last three decades, supercomputers have gotten about 10 times faster every four years or so. And the stewards of these machines are already planning the next models: Oak Ridge engineers are designing a supercomputer that will be three to five times faster than Frontier, likely to be unveiled in the coming decade. 

But one big challenge looms: the energy footprint. Frontier, which already employs energy-conserving innovations, draws enough power even while idling to run thousands of homes. Engineers will need to figure out how to build these behemoths not just for speed, but for environmental sustainability. 

Article link: https://www.technologyreview.com/2024/01/08/1085128/exascale-computing-breakthrough-technologies/?

ESCAPE FIRE exposes the perverse nature of American healthcare, contrasting the powerful forces opposing change with the compelling stories of pioneering leaders and the patients they seek to help. The film is about finding a way out. It’s about saving the health of a nation.

September 19, 2024

AUTHORS

David Blumenthal, Evan D. Gumas,Arnav Shah, Munira Z. Gunja,Reginald D. Williams II

DOWNLOADS:

• Fund Report ↓
• Chartpack (pdf) ↓
• Chartpack (ppt) ↓
• News Release ↓

The U.S. health care system is failing to keep Americans healthy, ranking last in a new Commonwealth Fund report that compares health and health care in 10 countries. U.S. performance is particularly poor when it comes to health equity, access to care, efficiency, and health outcomes. 

According to Mirror, Mirror 2024: A Portrait of the Failing U.S. Health System, the U.S. spends the most on health care, yet Americans live shorter, less healthy lives than people in Australia, Canada, France, Germany, the Netherlands, New Zealand, Sweden, Switzerland, and the United Kingdom. Other key findings:  

• Americans experience the most difficulties getting and affording health care.  
• The U.S. and New Zealand rank lowest on health equity, meaning they have the largest income-related differences in key measures of health system performance, and more of their residents face unfair treatment and discrimination when seeking care compared to residents of the other countries. 
• Patients and physicians in the U.S. face the most onerous billing and payment burdens, leading to poor performance on measures of administrative efficiency. 

“The U.S. continues to be in a class by itself in the underperformance of its health care sector,” say the study’s authors, who call for policymakers and health care leaders to learn from other countries’ experiences and act. 

Article link: https://www.commonwealthfund.org/publications/fund-reports/2024/sep/mirror-mirror-2024

By Courtney Albon

 Friday, Sep 13, 2024

Since transitioning most of its 5G research and development projects to the Chief Information Office last year, the Pentagon’s Future Generation Wireless Technology Office has shifted its focus to preparing the Defense Department for the next wave of network innovation.

That work is increasingly important for the U.S., which is racing against China to shape the next iteration of wireless telecommunications, known as 6G. These more advanced networks, expected to materialize in the 2030s, will pave the way for more dependable high-speed, low-latency communication and could support the Pentagon’s technology interests — from robotics and autonomy to virtual reality and advanced sensing.

Staying ahead means not only fostering technology development and industry standards but making sure that policy and regulations are in place to safely use the capability, according to Thomas Rondeau, who leads the Pentagon’s FutureG office. Staking a leadership role in the global competition, he said, could give DOD a level of control over what that future infrastructure looks like.

“If we can define those going into it, then as we export our technologies, we’re also exporting our policies and our regulations, because they’re going to be inherently part of those technology solutions,” Rondeau told Defense News in a recent interview.

The Defense Department started making a concerted investment in 5G about five years ago when then Undersecretary of Research and Engineering Michael Griffin named the technology a top priority for the Pentagon.

In 2020, DOD awarded contracts totaling $600 million to 15 companiesto experiment with various 5G applications at five bases around the country. The projects included augmented and virtual reality training, smart warehousing, command and control and spectrum utilization.

The department has since expanded the pilots and pursued other wireless network development projects, including a 5G Challenge series that incentivized companies to move toward more open-access networks.

The result has, so far, been a mixed bag. Most of the pilots didn’t transition into formal programs within the military services, Rondeau said. Several of the failed efforts involved commercial augmented or virtual reality technology that wasn’t mature enough for DOD to justify continued funding.

Among the projects that did transfer, Rondeau highlighted a pilot effort at Naval Air Station Whidbey Island in Washington to provide fixed wireless access to the base. The project essentially replaced hundreds of pounds of cables with radio units that broadcast the communications network to the personnel who need it. Today, the system is supporting logistics and maintenance operations at the base.

“This could be a huge benefit for readiness, but also I think it should be very cost-effective way to slim down on everything that you pay for cables,” Rondeau said. “That will be a continued, sustainable project.”

This and other transitioned pilots will likely make their way into a formal budget cycle by fiscal 2027, he added.

DOD also saw some success from the 5G Challenges it staged in 2022 and 2023 to encourage telecommunication companies to transition to an open radio access network, or O-RAN. A RAN is the first entry point a wireless device makes into a network and accounts for about 80% of its cost. Historically, proprietary RANs managed by companies like Huawei, Ericsson, Nokia and Samsung have dominated the market.

“They’re driving a world where they control the entire system, the end-to-end system,” Rondeau said. “That causes a lack of insight, a lack of innovation on our side, and it causes challenges with how to apply these types of systems to unique, niche military needs.”

The 5G Challenge offered companies a chance to break open that proprietary model by moving to O-RANS — and according to Rondeau, it was a success. The initial challenge then expanded into a broader forum that addressed issues like energy efficiency and spectrum management. Ultimately, the effort reduced energy usage by around 30%, he said.

Rondeau said that while much of the focus of these initiatives was on 5G, the work has informed the Pentagon’s vision and strategy for 6G, which the department believes should have an open-source foundation.

“That is a direct result of not only my background and push for some of these things, but also the learnings that we got from the networks we’ve deployed, from the 5G Challenge,” he said. “All these things come into play that led us towards an open-source software model being the right model for the military and, we think, for industry.”

One of the FutureG office’s top priorities these days, a direct outgrowth of the 5G Challenge, is called CUDU, which stands for centralized unit, distributed unit. The project is focused on implementing a fully open software model for 6G that meets the needs of industry, the research community and DOD.

The office is also exploring how the military could use 6G for sensing and monitoring. Its Integrated Sensing and Communications project, dubbed ISAC, uses wireless signals to collect information about different environments. That capability could be used to monitor drone networks or gather military intelligence.

While ISAC technology could bring a major boost to DOD’s ISR systems, commercialization could make it accessible to adversary nations who might weaponize it against the U.S. That challenge reflects a broader DOD concern around 6G policies and regulation – and drives urgency within Rondeau’s office to ensure the U.S. is the first to shape the foundation of these next-generation networks.

“We’re looking at this as a real opportunity for dramatic growth and interest in new, novel technologies for both commercial industry and defense needs,” he said. “But also, the threat space that it opens up for us is potentially pretty dramatic, so we need to be on top of this.”

Article link: https://www.defensenews.com/pentagon/2024/09/13/pentagon-readies-for-6g-the-next-of-wave-of-wireless-network-tech/