#infrastructure models

[mostlysignssomeportents]

Elizabeth Warren on weaponized budget models

In yesterday’s essay, I broke down the new series from The American Prospect on the hidden ideology and power of budget models, these being complex statistical systems for weighing legislative proposals to determine if they are “economically sound.” The assumptions baked into these models are intensely political, and, like all dirty political actors, the model-makers claim they are “empirical” while their adversaries are “doing politics”:

https://pluralistic.net/2023/04/03/all-models-are-wrong/#some-are-useful

If you’d like an essay-formatted version of this post to read or share, here’s a link to it on pluralistic.net, my surveillance-free, ad-free, tracker-free blog:

https://pluralistic.net/2023/04/04/cbo-says-no/#wealth-tax

Today edition of the Prospect continues the series with an essay by Elizabeth Warren, describing how her proposal for universal child care was defeated by the incoherent, deeply political assumptions of the Congressional Budget Office’s model, blocking an important and popular policy simply because “computer says no”:

https://prospect.org/economy/2023-04-04-policymakers-fight-losing-battle-models/

When the Build Back Better bill was first mooted, it included a promise of universal, federally funded childcare. This was excised from the final language of the bill (renamed the Bipartisan Infrastructure Bill), because the CBO said it would cost too much: $381.5b over ten years.

This is a completely nonsensical number, and the way that CBO arrived at it is illuminating, throwing the ideology of CBO modeling into stark relief. You see, the price tag for universal childcare did not include the benefits of childcare!

As Warren points out, this is not how investment works. No business leader assesses their capital expenditures without thinking of the dividends from those investments. No firm decides whether to open a new store by estimating the rent and salaries and ignoring the sales it will generate. Any business that operates on that basis would never invest in anything.

Universal childcare produces enormous dividends. Kids who have access to high-quality childcare grow up to do better in school, have less trouble with the law, and earn more as adults. Mothers who can’t afford childcare, meanwhile, absent themselves from the workforce during their prime earning years. Those mothers are less likely to advance professionally, have lower lifetime earnings, and a higher likelihood of retiring without adequate savings.

What’s more, universal childcare is the only way to guarantee a living wage to childcare workers, who are disproportionately likely to rely on public assistance, including SNAP (AKA food stamps) to make ends meet. These stressors affect childcare workers’ job performance, and also generate public expenditures to keep those workers fed and housed.

But the CBO model does not include any of those benefits. As Warren says, in a CBO assessment, giving every kid in America decent early childhood care and every childcare worker a living wage produces the same upside as putting $381.5 in a wheelbarrow and setting it on fire.

This is by design. Congress has decreed that CBO assessments can’t factor in secondary or indirect benefits from public expenditure. This is bonkers. Public investment is all secondary and indirect benefits���— from highways to broadband, from parks to training programs, from education to Medicare. Excluding indirect benefits from assessments of public investments is a literal, obvious, unavoidable recipe for ending the most productive and beneficial forms of public spending.

It means that — for example — a CBO score for Meals on Wheels for seniors is not permitted to factor in the Medicare savings from seniors who can age in their homes with dignity, rather than being warehoused at tremendous public expense in nursing homes.

It means that the salaries of additional IRS enforcers can only be counted as an expense — Congress isn’t allowed to budget for the taxes that those enforcers will recover.

And, of course, it’s why we can’t have Medicare For All. Private health insurers treat care as an expense, with no upside. Denying you care and making you sicker isn’t a bug as far as the health insurance industry is concerned — it’s a feature. You bear the expense of the sickness, after all, and they realize the savings from denying you care.

But public health programs can factor in those health benefits and weigh them against health costs — in theory, at least. However, if the budgeting process refuses to factor in “indirect” benefits — like the fact that treating your chronic illness lets you continue to take care of your kids and frees your spouse from having to quit their job to look after you — then public health care costings become indistinguishable from the private sector’s for-profit death panels.

Child care is an absolute bargain. The US ranks 33d out of 37 rich countries in terms of public child care spending, and in so doing, it kneecaps innumerable mothers’ economic prospects. The upside of providing care is enormous, far outweighing the costs — so the CBO just doesn’t weigh them.

Warren is clear that there’s no way to make public child care compatible with CBO scoring. Even when she whittled away at her bill, excluding millions of families who would have benefited from the program, the CBO still flunked it.

The current budget-scoring system was designed for people who want to “shrink government until it fits in a bathtub, and then drown it.” It is designed so that we can’t have nice things. It is designed so that the computer always says no.

Warren calls for revisions to the CBO model, to factor in those indirect benefits that are central to public spending. She also calls for greater diversity in CBO oversight, currently managed by a board of 20 economists and only two non-economists — and the majority of the economists got their PhDs from the same program and all hew to the same orthodoxy.

For all its pretense of objectivity, modeling is a subjective, interpretive discipline. If all your modelers are steeped in a single school, they will incinerate the uncertainty and caveats that should be integrated into every modeler’s conclusions, the humility that comes from working with irreducible uncertainty.

Finally, Warren reminds us that there are values that are worthy of consideration, beyond a dollars-and-cents assessment. Even though programs like child care pay for themselves, that’s not the only reason to favor them — to demand them. Child care creates “an America in which everyone has opportunities — and ‘everyone’ includes mamas.” Child care is “an investment in care workers, treating them with respect for the hard work they do.”

The CBO’s assassination of universal child care is exceptional only because it was a public knifing. As David Dayen and Rakeen Mabud wrote in their piece yesterday, nearly all of the CBO’s dirty work is done in the dark, before a policy is floated to the public:

https://prospect.org/economy/2023-04-03-hidden-in-plain-sight/

The entire constellation of political possibility has been blotted out by the CBO, so that when we gaze up at the sky, we can only see a few sickly stars — weak economic nudges like pricing pollution, and not the glittering possibilities of banning it. We see the faint hope of “bending the cost-curve” on health care, and not the fierce light of simply providing care.

We can do politics. We have done it before. Every park and every highway, our libraries and our schools, our ports and our public universities — these were created by people no smarter than us. They didn’t rely on a lost art to do their work. We know how they did it. We know what’s stopping us from doing it again. And we know what to do about it.

Have you ever wanted to say thank you for these posts? Here’s how you can: I’m kickstarting the audiobook for my next novel, a post-cyberpunk anti-finance finance thriller about Silicon Valley scams called Red Team Blues. Amazon’s Audible refuses to carry my audiobooks because they’re DRM free, but crowdfunding makes them possible.

[Image ID: A disembodied hand, floating in space. It holds a Univac mainframe computer. The computer is shooting some kind of glowing red rays that are zapping three US Capitol Buildings, suspended on hovering platforms. In the background, the word NO is emblazoned in a retrocomputing magnetic ink font, limned in red.]

[deadpanwalking]

At least tell me you're still gonna vote

It's not 2016 anymore, man. I've changed my whole shit around. I've actually been a leftist for quite some time, and believe me when I say I'm beyond done shilling for the Democratic establishment. Under the guise of "civic engagement", my leftoid commie friends and I have infiltrated the system and are gonna flood the market with potential non-voters.

Here's the deal.

You know how I've been a CASA for almost a decade? Well, my friend tipped me off about the local chapter of Black & Pink/ FJAH—I got involved ostensibly because I'm outraged by the violence and racism woven into the fabric of the justice system ruining the lives of entire generations of families. As I've been volunteering for Ayanna Pressley's election campaigns since her Boston City Council days, I've been lowkey spreading the prison abolitionist agenda by talking up the importance of the Inclusive Democracy Act—which would end felony disenfranchisement—when I tell people about Pressley's progressive policies. Now, that may sound extremely vote-pilled at first, but in the long run it accomplishes the most important leftist objective of all: suffrage gives 4.6 million people the choice not to vote.

I'm also continuing to help immigrant and refugee families navigate the byzantine naturalization/citizenship application process via the same organization that my grandmother volunteered for when she was alive. This may also veer dangerously close to patriotism (the amount of American propaganda I have to push to help them pass the civics exam is excruciating), but bear in mind that many of the freshly minted citizens will forgo voting entirely because they're just happy to be living large on Uncle Sam's handouts, and the rest are rabid Zionists who believe that "эта проститутка" (Hillary Rodham Clinton, age 76, public speaker, grandmother of 3) is an active threat to society, and are chomping at the bit to vote for Trump this and every subsequent November.

This is how we win.

[anny-chovy]

Denis Goldschmidt / 1970

[paradife-loft]

do I have homework for my econ class I need to be doing? yes

did I just spend 20 minutes making this instead? also yes

[vermillioncrown]

i've been looking at this motherfucking excel sheet for three weeks now

[jcmarchi]

Open-Source Platform Cuts Costs for Running AI - Technology Org

New Post has been published on https://thedigitalinsider.com/open-source-platform-cuts-costs-for-running-ai-technology-org/

Open-Source Platform Cuts Costs for Running AI - Technology Org

Cornell researchers have released a new, open-source platform called Cascade that can run artificial intelligence (AI) models in a way that slashes expenses and energy costs while dramatically improving performance.

Artificial intelligence hardware – artistic interpretation. Image credit: Alius Noreika, created with AI Image Creator

Cascade is designed for settings like smart traffic intersections, medical diagnostics, equipment servicing using augmented reality, digital agriculture, smart power grids and automatic product inspection during manufacturing – situations where AI models must react within a fraction of a second. It is already in use by College of Veterinary Medicine researchers monitoring cows for risk of mastitis.

With the rise of AI, many companies are eager to leverage new capabilities but worried about the associated computing costs and the risks of sharing private data with AI companies or sending sensitive information into the cloud – far-off servers accessed through the internet.

Also, today’s AI models are slow, limiting their use in settings where data must be transferred back and forth or the model is controlling an automated system. 

A team led by Ken Birman, professor of computer science in the Cornell Ann S. Bowers College of Computing and Information Science, combined several innovations to address these concerns.

Birman partnered with Weijia Song, a senior research associate, to develop an edge computing system they named Cascade. Edge computing is an approach that places the computation and data storage closer to the sources of data, protecting sensitive information. Song’s “zero copy” edge computing design minimizes data movement.

The AI models don’t have to wait to fetch data when reacting to an event, which enables faster responses, the researchers said.

“Cascade enables users to put machine learning and data fusion really close to the edge of the internet, so artificially intelligent actions can occur instantly,” Birman said. “This contrasts with standard cloud computing approaches, where the frequent movement of data from machine to machine forces those same AIs to wait, resulting in long delays perceptible to the user.” 

Cascade is giving impressive results, with most programs running two to 10 times faster than cloud-based applications, and some computer vision tasks speeding up by factors of 20 or more. Larger AI models see the most benefit.

Moreover, the approach is easy to use: “Cascade often requires no changes at all to the AI software,” Birman said.

Alicia Yang, a doctoral student in the field of computer science, was one of several student researchers in the effort. She developed Navigator, a memory manager and task scheduler for AI workflows that further boosts performance.

“Navigator really pays off when a number of applications need to share expensive hardware,” Yang said. “Compared to cloud-based approaches, Navigator accomplishes the same work in less time and uses the hardware far more efficiently.”

In CVM, Parminder Basran, associate research professor of medical oncology in the Department of Clinical Sciences, and Matthias Wieland, Ph.D. ’21, assistant professor in the Department of Population Medicine and Diagnostic Sciences, are using Cascade to monitor dairy cows for signs of increased mastitis – a common infection in the mammary gland that reduces milk production.

By imaging the udders of thousands of cows during each milking session and comparing the new photos to those from past milkings, an AI model running on Cascade identifies dry skin, open lesions, rough teat ends and other changes that may signal disease. If early symptoms are detected, cows could be subjected to a medicinal rinse at the milking station to potentially head off a full-blown infection.

Thiago Garrett, a visiting researcher from the University of Oslo, used Cascade to build a prototype “smart traffic intersection.”

His solution tracks crowded settings packed with people, cars, bicycles and other objects, anticipates possible collisions and warns of risks – within milliseconds after images are captured. When he ran the same AI model on a cloud computing infrastructure, it took seconds to sense possible accidents, far too late to sound a warning.

With the new open-source release, Birman’s group hopes other researchers will explore possible uses for Cascade, making AI applications more widely accessible.

“Our goal is to see it used,” Birman said. “Our Cornell effort is supported by the government and many companies. This open-source release will allow the public to benefit from what we created.”

Source: Cornell University

You can offer your link to a page which is relevant to the topic of this post.

[asmuchasidliketo]

Tagged by @cantteachanoldguardnewquotes, thank you! 😘

name: Matteic

when is your birthday? Once a year 😉 (thank you for the idea, person I reblogged from!)

where are you from originally? France (center north)

where do you live now? France (south east)

your sun sign & MBTI personality type: Non practising, and ISTJ-adjacent

your first OTP: Uhhh probably Mulder and Scully

your current OTP: Hmm… I'll say Steve and Danny in Hawaii 5-0, but I don't pay much attention to it (I'm aroace)

you’re granted the ability to control one of the elements, which one do you choose? Earth sounds cool

a place you want to visit before you die: a house of my parent's friends, just to see how it looks like as an adult

your friends are taking you to Disneyland, but you have to dress up as a character to get in. who do you pick? The yo-yo flamingo from Fantasia 2000. I'm even ready to learn how to use a yo-yo. Yes, I'm serious. 🦩

the last text you sent and who you sent it to: My niece, to ask her what kind of book she wants for her birthday

[sebdoeswords]

I just want to say if you're American and the media you write for is not from or set in the US (or is set in a fantasy world that's not modelled after the US) don't americanise your modern AUs!!! It's extremely disrespectful to the people and cultures of where the media is originally from!

Get out of your comfort zone! Learn about other countries and other lifestyles! Don't turn everything into generic white picket fence US suburbia!!

I just wanna say, if you aren't American, definitely try setting a modern AU in your country. Fill it with the things you know, to breathe life into it. It's really nice to see new settings, to open up a fic and go 'oh wait, hold up, I know that place'. It might only apply to a few people who read your fic but it's really rewarding to get that feedback.

(Americans keep doing you, just trying to encourage the rest of us lol)

[idea-explorer]

[ethyrialpharmaceutical]

The PCD Pharma Franchise model has been gaining traction in India due to its low investment and high potential for profit. Karnataka, known for its strong industrial base and growing healthcare infrastructure, is an ideal location for those looking to start a PCD pharma business. In this article, we will explore the potential of the PCD Pharma Franchise in Karnataka, the benefits of starting one, and the step-by-step process to get started.

[sapphia]

USA please listen to me: the price of “teaching them a lesson” is too high. take it from New Zealand, who voted our Labour government out in the last election because they weren’t doing exactly what we wanted and got facism instead.

Trans rights are being attacked, public transport has been defunded, tax cuts issued for the wealthy, they've mass-defunded public services, cut and attacked the disability funding model, cut benefits, diverted transport funding to roads, cut all recent public transport subsidies, cancelled massive important infrastructure projects like damns and ferries (we are three ISLANDS), fast tracked mining, oil, and other massive environmentally detrimental projects and gave the power the to approve these projects singularly to three ministers who have been wined and dined by lobbyists of the companies that have put the bids in to approve them while one of the main minister infers he will not prioritise the protection of endangered species like the archeys frog over mining projects that do massive environmental harm. They have attacked indigenous rights in an attempt to negate the Treaty of Waitangi by “redefining it”; as a backup, they are also trying to remove all mentions of the treaty from legislation starting with our Child Protection laws no longer requiring social workers to consider the importance of Maori children’s culture when placing those children; when the Waitangi Tribunal who oversees indigenous matters sought to enquire about this, the Minister for Children blocked their enquiry in a breach of comity that was condemned in a ruling — too late to do anything — by our Supreme Court. They have repealed labour protections around pay and 90 day trials, reversed our smoking ban, cancelled our EV subsidy, cancelled our water infrastructure scheme that would have given Maori iwi a say in water asset management, cancelled our biggest city’s fuel tax, made our treasury and inland revenue departments less accountable, dispensed of our Productivity Commission, begun work on charter schools and military boot camps in an obvious push towards privatisation, cancelled grants for first home buyers, reduced access to emergency housing, allowed no cause evictions, cancelled our Maori health system that would have given Maori control over their own public medical care and funding, cut funding of services like budgeting advice and food banks, cancelled the consumer advocacy council, cancelled our medicine regulations, repealed free prescriptions, deferred multiple hospital builds, failed to deliver on pre-election medical promises, reversed a gun ban created in response to the mosque shootings, brought back three strikes = life sentence policy, increased minimum wage by half the recommended amount, cancelled fair pay for disabled workers, reduced wheelchair services, reversed our oil and gas exploration ban, cancelled our climate emergency fund, cut science research funding including climate research, removed limits on killing sea lions, cut funding for the climate change commission, weakened our methane targets, cancelled Significant National Areas protections, have begun reversing our ban on live exports. Much of this was passed under urgency.

It’s been six months.

[seowhrgddd]

Building Information Modeling for Infrastructure

Next Gen AEC is a group company of HC Robotics and Centillion Solutions, a leading company in the construction technology and building automation sectors. We leverage the combined expertise and resources of our group companies to deliver innovative solutions for the Architecture, Engineering and Construction (AEC) industry. VISIT - https://www.nextgenaec.com/bim-modeling/

[novelistparty]

you know how scifi novels always have people in the far future speaking "common" or "basic" or whatever universal language? in science that is matlab. it is a wildly purchasable "common". a truly majestic example of how to make a product guaranteed to be in every science budget. it's like someone figured out how to charge for the english language

[townpostin]

Tribal University and Engineering College Planned for Ghatshila

Ramdas Soren announces education initiatives; PPP model hospital also in the works Ghatshila MLA Ramdas Soren unveils plans for Tribal University, Engineering College, and PPP model hospital in the region. GHATSHILA – Cabinet Minister Ramdas Soren reveals plans for a Tribal University in Ghatshila and an Engineering College in Musabani. During a visit to Musabani, Cabinet Minister and Ghatshila…

[nnctales]

Latest Construction News Ongoing Around the World

The construction industry is undergoing significant changes globally, driven by technological advancements, sustainability initiatives, and evolving market dynamics. This article explores the latest construction news and ongoing projects around the world, highlighting key developments, challenges, and trends shaping the future of the industry. Major Ongoing Projects in Construction News 1. Saudi…

[jcmarchi]

David Maher, CTO of Intertrust – Interview Series

New Post has been published on https://thedigitalinsider.com/david-maher-cto-of-intertrust-interview-series/

David Maher, CTO of Intertrust – Interview Series

David Maher serves as Intertrust’s Executive Vice President and Chief Technology Officer. With over 30 years of experience in trusted distributed systems, secure systems, and risk management Dave has led R&D efforts and held key leadership positions across the company’s subsidiaries. He was past president of Seacert Corporation, a Certificate Authority for digital media and IoT, and President of whiteCryption Corporation, a developer of systems for software self-defense. He also served as co-chairman of the Marlin Trust Management Organization (MTMO), which oversees the world’s only independent digital rights management ecosystem.

Intertrust developed innovations enabling distributed operating systems to secure and govern data and computations over open networks, resulting in a foundational patent on trusted distributed computing.

Originally rooted in research, Intertrust has evolved into a product-focused company offering trusted computing services that unify device and data operations, particularly for IoT and AI. Its markets include media distribution, device identity/authentication, digital energy management, analytics, and cloud storage security.

How can we close the AI trust gap and address the public’s growing concerns about AI safety and reliability?

Transparency is the most important quality that I believe will help address the growing concerns about AI. Transparency includes features that help both consumers and technologists understand what AI mechanisms are part of systems we interact with, what kind of pedigree they have: how an AI model is trained, what guardrails exist, what policies were applied in the model development, and what other assurances exist for a given mechanism’s safety and security.  With greater transparency, we will be able to address real risks and issues and not be distracted as much by irrational fears and conjectures.

What role does metadata authentication play in ensuring the trustworthiness of AI outputs?

Metadata authentication helps increase our confidence that assurances about an AI model or other mechanism are reliable. An AI model card is an example of a collection of metadata that can assist in evaluating the use of an AI mechanism (model, agent, etc.) for a specific purpose. We need to establish standards for clarity and completeness for model cards with standards for quantitative measurements and authenticated assertions about performance, bias, properties of training data, etc.

How can organizations mitigate the risk of AI bias and hallucinations in large language models (LLMs)?

Red teaming is a general approach to addressing these and other risks during the development and pre-release of models. Originally used to evaluate secure systems, the approach is now becoming standard for AI-based systems. It is a systems approach to risk management that can and should include the entire life cycle of a system from initial development to field deployment, covering the entire development supply chain. Especially critical is the classification and authentication of the training data used for a model.

What steps can companies take to create transparency in AI systems and reduce the risks associated with the “black box” problem?

Understand how the company is going to use the model and what kinds of liabilities it may have in deployment, whether for internal use or use by customers, either directly or indirectly. Then, understand what I call the pedigrees of the AI mechanisms to be deployed, including assertions on a model card, results of red-team trials, differential analysis on the company’s specific use, what has been formally evaluated, and what have been other people’s experience. Internal testing using a comprehensive test plan in a realistic environment is absolutely required. Best practices are evolving in this nascent area, so it is important to keep up.

How can AI systems be designed with ethical guidelines in mind, and what are the challenges in achieving this across different industries?

This is an area of research, and many claim that the notion of ethics and the current versions of AI are incongruous since ethics are conceptually based, and AI mechanisms are mostly data-driven. For example, simple rules that humans understand, like “don’t cheat,” are difficult to ensure. However, careful analysis of interactions and conflicts of goals in goal-based learning, exclusion of sketchy data and disinformation, and building in rules that require the use of output filters that enforce guardrails and test for violations of ethical principles such as advocating or sympathizing with the use of violence in output content should be considered. Similarly, rigorous testing for bias can help align a model more with ethical principles. Again, much of this can be conceptual, so care must be given to test the effects of a given approach since the AI mechanism will not “understand” instructions the way humans do.

What are the key risks and challenges that AI faces in the future, especially as it integrates more with IoT systems?

We want to use AI to automate systems that optimize critical infrastructure processes. For example, we know that we can optimize energy distribution and use using virtual power plants, which coordinate thousands of elements of energy production, storage, and use. This is only practical with massive automation and the use of AI to aid in minute decision-making. Systems will include agents with conflicting optimization objectives (say, for the benefit of the consumer vs the supplier). AI safety and security will be critical in the widescale deployment of such systems.

What type of infrastructure is needed to securely identify and authenticate entities in AI systems?

We will require a robust and efficient infrastructure whereby entities involved in evaluating all aspects of AI systems and their deployment can publish authoritative and authentic claims about AI systems, their pedigree, available training data, the provenance of sensor data, security affecting incidents and events, etc. That infrastructure will also need to make it efficient to verify claims and assertions by users of systems that include AI mechanisms and by elements within automated systems that make decisions based on outputs from AI models and optimizers.

Could you share with us some insights into what you are working on at Intertrust and how it factors into what we have discussed?

We research and design technology that can provide the kind of trust management infrastructure that is required in the previous question. We are specifically addressing issues of scale, latency, security and interoperability that arise in IoT systems that include AI components.

How does Intertrust’s PKI (Public Key Infrastructure) service secure IoT devices, and what makes it scalable for large-scale deployments?

Our PKI was designed specifically for trust management for systems that include the governance of devices and digital content. We have deployed billions of cryptographic keys and certificates that assure compliance. Our current research addresses the scale and assurances that massive industrial automation and critical worldwide infrastructure require, including best practices for “zero-trust” deployments and device and data authentication that can accommodate trillions of sensors and event generators.

What motivated you to join NIST’s AI initiatives, and how does your involvement contribute to developing trustworthy and safe AI standards?

NIST has tremendous experience and success in developing standards and best practices in secure systems. As a Principal Investigator for the US AISIC from Intertrust, I can advocate for important standards and best practices in developing trust management systems that include AI mechanisms. From past experience, I particularly appreciate the approach that NIST takes to promote creativity, progress, and industrial cooperation while helping to formulate and promulgate important technical standards that promote interoperability. These standards can spur the adoption of beneficial technologies while addressing the kinds of risks that society faces.

Thank you for the great interview, readers who wish to learn more should visit Intertrust.