Unveiling the Top AI Development Technologies | by Pratik Rupareliya

Bringing Generative Artificial Intelligence To Space

TAMPA, Fla. — Amazon Web Services is busy positioning its cloud infrastructure business to capitalize on the promise of generative artificial intelligence for transforming space and other industries.

More than 60% of the company's space and aerospace customers are already using some form of AI in their businesses, according to AWS director of aerospace and satellite Clint Crosier, up from single digits around three years ago.

Crosier predicts similar growth over the next few years in space for generative AI, which uses deep-learning models to answer questions or create content based on patterns detected in massive datasets, marking a major step up from traditional machine-learning algorithms.

Mathematical advances, an explosion in the amount of available data and cheaper and more efficient chips for processing it are a "perfect storm" for the rise of generative AI, he told SpaceNews in an interview, helping drive greater adoption of cloud-based applications.

"In the last year, AWS has fundamentally reorganized itself internally so that we could put the right teams [and] organizational structure in place … so that we can really double down on generative AI," he said.

He said AWS has created a "generative AI for space" cell of a handful of people to engage with cloud customers to help develop next-generation capabilities.

These efforts include a generative AI laboratory for customers to experiment with new ways of using these emerging capabilities. 

Crosier sees three main areas for using generative AI in space: geospatial analytics, spacecraft design and constellation management.

Earth observation satellite operators such as BlackSky and Capella Space already use these tools to help manage search queries and gain more insights into their geospatial data.

It's early days in the manufacturing sector, but Crosier said engineers are experimenting with how a generative AI model fed with design parameters could produce new concepts by drawing from potentially overlooked data, such as from the automotive industry.

"Whether you're designing a satellite, rocket or spacecraft, you're letting the generative AI go out and do that exploratory work around the globe with decades of data," he said, "and then it will come back and bring you novel design concepts that nobody has envisioned before for your team to use as a baseline to start refining."

He said generative AI also has the potential to help operators manage increasingly crowded orbits by helping to simulate testing scenarios.

"If I have a constellation of 600 satellites, I want to model how that constellation will behave under various design parameters," he said. 

"Well, I can get a model of two concepts, which leaves me woefully inadequate — but it costs time and money to model them, or I can model an infinite number. Gen AI will tell me what are the top 25 cases I should model for my modeling simulation capability that will give me the best design optimization, and so we're seeing it used that way."

AWS efforts to accelerate the adoption of these emerging computing capabilities also include scholarships and a commitment announced in November to provide free AI training for two million people worldwide before the end of 2025.

Potential Power And Pitfalls Of Harnessing Artificial Intelligence For Sleep Medicine

In a new research commentary, the Artificial Intelligence in Sleep Medicine Committee of the American Academy of Sleep Medicine highlights how artificial intelligence stands on the threshold of making monumental contributions to the field of sleep medicine. Through a strategic analysis, the committee examined advancements in AI within sleep medicine and spotlighted its potential in revolutionizing care in three critical areas: clinical applications, lifestyle management, and population health. The committee also reviewed barriers and challenges associated with using AI-enabled technologies.

"AI is disrupting all areas of medicine, and the future of sleep medicine is poised at a transformational crossroad," said lead author Dr. Anuja Bandyopadhyay, chair of the Artificial Intelligence in Sleep Medicine Committee. "This commentary outlines the powerful potential and challenges for sleep medicine physicians to be aware of as they begin leveraging AI to deliver precise, personalized patient care and enhance preventive health strategies on a larger scale while ensuring its ethical deployment."

According to the authors, AI has potential uses in the sleep field in three key areas:

Clinical Applications:In the clinical realm, AI-driven technologies offer comprehensive data analysis, nuanced pattern recognition and automation in diagnosis, all while addressing chronic problems like sleep-related breathing disorders. Despite understated beginnings, the utilization of AI can offer improvements in efficiency and patient access, which can contribute to a reduction in burnout among health care professionals.

Lifestyle Management:Incorporating AI also offers clear benefits for lifestyle management through the use of consumer sleep technology. These devices come in various forms like fitness wristbands, smartphone apps, and smart rings, and they contribute to better sleep health through tracking, assessment and enhancement. Wearable sleep technology and data-driven lifestyle recommendations can empower patients to take an active role in managing their health, as shown in a recent AASM survey, which reported that 68% of adults who have used a sleep tracker said they have changed their behavior based on what they have learned. But, as these AI-driven applications grow ever more intuitive, the importance of ongoing dialogue between patients and clinicians about the potential and limitations of these innovations remains vital.

Population Health: Beyond individual care, AI technology reveals a new approach to public health regarding sleep. "AI has the exciting potential to synthesize environmental, behavioral and physiological data, contributing to informed population-level interventions and bridging existing health care gaps," noted Bandyopadhyay.

The paper also offers warnings about the integration of AI into sleep medicine. Issues of data privacy, security, accuracy, and the potential for reinforcing existing biases present new challenges for health care professionals. Additionally, reliance on AI without sufficient clinical judgment could lead to complexities in patient treatment.

"While AI can significantly strengthen the evaluation and management of sleep disorders, it is intended to complement, not replace, the expertise of a sleep medicine professional," Bandyopadhyay stated.

Navigating this emerging landscape requires comprehensive validation and standardization protocols to responsibly and ethically implement AI technologies in health care. It's critical that AI tools are validated against varied datasets to ensure their reliability and accuracy in all patient populations.

"Our commentary provides not just a vision, but a roadmap for leveraging the technology to promote better sleep health outcomes," Bandyopadhyay said. "It lays the foundation for future discussions on the ethical deployment of AI, the importance of clinician education, and the harmonization of this new technology with existing practices to optimize patient care."

Should The Federal Government Regulate Artificial Intelligence?

WASHINGTON, DC - OCTOBER 30: U.S. President Joe Biden hands Vice President Kamala Harris the pen he ... [+] used to sign a new executive order regarding artificial intelligence during an event in the East Room of the White House on October 30, 2023 in Washington, DC. President Biden issued the executive order directing his administration to create a new chief AI officer, track companies developing the most powerful AI systems, adopt stronger privacy policies and "both deploy AI and guard against its possible bias," creating new safety guidelines and industry standards. (Photo by Chip Somodevilla/Getty Images)

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Artificial intelligence is in the public policy spotlight. In October 2023, the Biden Administration issued a Presidential Executive Order on AI directing federal agencies to cooperate in protecting the public from potential AI-related harms. President Biden said in his March 2024 State of the Union address that government enforcers will crack down on the use of AI to facilitate illegal price-fixing. Congress is in the preliminary stages of considering legislation that could pave the way for future regulation of AI.

The European Union went "one better" by adopting a far-reaching AI act in March 2024. It bans AI systems that are "considered to pose an unacceptable risk for the health, safety, and fundamental rights of individuals." The act also regulates general purpose AI models that can be applied to a wide variety of tasks, imposing obligations on them according to the level of risk they impose, or are believed to impose, on the public.

Should the federal government follow in Europe's footsteps and adopt comprehensive AI regulation to forestall bad conduct? The short answer is no, not at this time.

Laws Already On The Books Disincentivize AI Abuses

First, keep in mind that AI, like all other technologies, is already fully subject to generally applicable U.S. Criminal and civil laws.

Indeed, the 2023 AI Executive Order highlighted the application of these laws (which address civil rights, national security, antitrust, privacy, labor rights, health care, and foreign affairs) to challenge the full array of potential AI abuses.

This is more than rhetoric. The Justice Department, for example, is reported to be "escalating" its antitrust probe of a criminal scheme to raise and fix rental housing prices with the use of AI algorithmic software. And in January 2024, the Federal Trade Commission announced it was investigating the competitive effects of AI-related partnerships and investments.

These and similar government initiatives send a strong signal to AI developers to avoid harmful conduct.

Regulation Is The Foe Of Innovation And Economic Growth

Case-by-case enforcement of general laws allows specific business abuses to be targeted and addressed, without otherwise interfering in business planning and initiatives.

Regulation, by contrast, establishes a framework of rules governing private sector conduct. Too often, this turns into inflexible, one-size-fits-all approaches which can ignore specific commercial circumstances and fail to respond in a timely manner to changes in technology and the business environment. Often, it's the already-entrenched business interests which benefit by leveraging their influence and manipulating this regulation to maintain their advantages.

A statistical analysis published in 2017 in the Journal of Regulatory Economics found that more-regulated industries had fewer new firms and slower employment growth in all firms. It also noted that "[l]arge firms may even successfully lobby government officials to increase regulations to raise their smaller rivals' costs."

Regulation also tends to reduce innovation, as found in a 2023 American Economic Review article. Innovation is a key to higher productivity and economic growth, as explained in a 2017 European Central Bank paper.

Those factors counsel strongly against rushing to regulate a new technology which is currently is accelerating innovation in a wide range of applications and may require new governing approaches, just as the commercialization of the internet once did. Specific cases spotlight the benefits of avoiding too-much, too-soon regulation.

American Internet Freedom Versus The EU's Stifling Approach

The U.S. Decision not to overregulate the internet in its infancy is a great public policy success that public policymakers examining AI should study closely. Economic analyst Mohamed Mouti explores the fruits of this decision in EconLog:

"In the mid-1990s, the Clinton administration made a wise choice. They declared the internet a 'market-driven area,' not regulated, with limited government involvement only to support and enforce a predictable, minimalist, consistent, and simple legal environment. This policy allowed a new generation of creative minds to explore this frontier for business and commerce. This approach led to the internet's success, resulting in a surge of innovation. Today, the US is home to the most innovative tech firms, hosting vibrant internet-based companies and bringing countless benefits to consumers and small businesses."

In contrast, the European Union, which favors the "precautionary principle" of avoiding risk through early adoption of regulation, has had a terrible innovation track record.

Take the case of the EU's efforts to regulate data privacy through its 2018 General Data Protection Regulation. GDPR requires firms to guarantee user rights related to access, consent, erasure, and data portability. There is already substantial evidence that it tends to impose high compliance costs and entrench incumbent companies, raise barriers to entry, and harm startups, entry, and smaller firms.

This history should give pause to anyone who believes that the AI Act will help position Europe to be an AI leader.

Is Now Really The Time?

Regulation is justified when its benefits can be shown to outweigh its costs. Of course, cost-benefit appraisals are imperfect and error-prone. In a famous 1969 article, the renowned economist Harold Demsetz warned against comparing an idealized version of a regulatory proposal (assuming it will work perfectly) to the actual outcomes of the current unregulated system.

The history of harmful regulatory imperfections underscores the wisdom of Demsetz's warning. U.S. Adoption of AI regulation would in all likelihood slow the rate of innovation in technology systems that appear poised to confer enormous benefits on society. Even small reductions in the AI growth rate can lead to huge long-term social welfare losses. Imagine what innovation-driven benefits might have been lost had the government decided to essentially control the internet 30 years ago.

What about AI-related harm? That is highly speculative at this point. Moreover, the federal government is closely monitoring the AI sector, ready to apply existing targeted legal sanctions at the first sign of a problem.

In sum, the AI landscape today features rapidly growing benefits and uncertain costs that, in all likelihood, can be well addressed under existing law if problems arise.

The time may (or may not) come when serious new and unanticipated AI-related problems arise that can best be handled through targeted regulatory solutions. But as of now, the case to regulate AI today has not been made.

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