#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.]

[aeolianblues]

Women?? On stage!!!? Holding microphones! Singing!! 😮Playing guitars!?? Drummers!!! 🤯Keyboardists 😱 Hoo boy I’m in heaven, hell yeah to women in bands 🤩

[economicsresearch]

page 566 - oh good idea, put some ice between those sticks. That's a nice bridge.

[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

[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.

[champstorymedia]

Autonomous Vehicle Infrastructure: Building the Roads of the Future

The advent of autonomous vehicles (AVs) is set to transform transportation as we know it. As technology rapidly evolves, the infrastructure that supports these self-driving cars must also be reimagined to ensure safety, efficiency, and sustainability. In this article, we will explore the concept of autonomous vehicle infrastructure, emphasizing the necessity of creating roads that accommodate AVs…

[prachicmi]

The Rise of Automated Machine Learning

Automated machine learning (AutoML) refers to the use of machine learning techniques to automate or partially automate the machine learning process. With AutoML, much of the tedious human involvement required for data preparation, model selection, hyperparameter tuning, and evaluation can be automated. Automated Machine Learning tool allows more resources to be devoted to understanding the problem domain and interpreting results, rather than manual trial-and-error in the ML workflow.

In the automated machine learning is revolutionizing how organizations both large and small can benefit from artificial intelligence. As these technologies continue to evolve, they hold much promise to automate routine data science work and improve ML productivity through means not feasible for human data scientists alone.

Get more insights on, Automated Machine Learning

[jimbuchan]

Perfection Raises Suspicions, Not Hopes

In just a short period of time, specifically over the last 2 years, Artificial Intelligence has given us a glimpse of the future of commerce, business and automation of everyday tasks. Much of this revolution has been borne from the advent of Generative AI tools such as ChatGPT and Grok, but while this technology saves us time in generating information, the promise of where AI is intended to go still has a lot of racetrack left. The Hollywood vision of AI as we have witnessed in movies with accurate prediction models and self-thinking robots continues to elude us, but this vision is approaching at a steady pace. In order to get us to this reality, the technology needs to be continually updated, and to which investors have responded in-kind spending hundreds of millions in both applications and hardware. Commensurate with the front-facing tools of AI is the huge power capacity in which to fuel this new infrastructure, which requires beefier processors and of course laser-fast raw internet speeds. On the latter, this is the current issue where we find ourselves with autonomous vehicles which at each millisecond needs to chow-down on fast speeds without hiccups, which enterprises such as Starlink is looking to remedy. Looking at the proliferation of AI for today’s Sales and Marketing efforts, much of the current buzz is with the automation of customer interaction such as contextual responses to emails, text-messages and chat-bots. While in the coming years, we may get to the point of trusting the ‘engine’ unconditionally to give us the correct sentimentality and tone with our responses back to the customer, the current state of generative content should be taken with a grain of salt. This is because some of the sauce within AI ‘hallucinates’ the feedback to the user, which may or may not be accurate. This is because the raw material that feeds the engine, which has been sourced from Large Language Models (LLM’s), has been trained to learn from existing sources (such as websites, books, literature and music) which makes ‘educated guesses’ based on prior answers. For the most part, the interpretations are fairly correct, but even if the accuracy level is 99.9%, do you risk having a .01 chance of an incorrect response provided to a customer?

You may have seen such glitches in AI-generated video clips or a repetitive response from a pizza delivery chat-bot. This is Artificial Intelligence 1.0, and like the first version of the web, will get better with time. So, looking for accuracy and precision at this particular time would be similar to expecting a full-scale e-Commerce site in 1995 when websites only had HTML. So, while some may criticize the inadequacies of AI, like any new technology the ones who lean-in early and go through the pain will realize the greatest benefits later on. Microsoft, Google, Salesforce and others all offer some sort of AI inherent within their platforms, be it search or within their CRM and the best way of becoming familiar is by adopting the technology and being a student, which will then provide you with ideas as to determine how it can benefit your business and/or your customer base. Just remember, like any new mechanism of progress (especially in the realm of the internet) the technology will continue to get better based on need and inventiveness, but in the short time that AI has gained steam, ignoring it could be your folly in just a few years from now.

__________________________________________________________________________________________ Title mage by Fuel Cells and Hydrogen Observatory | LLM segment by Flyte.org

[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/

[economicsresearch]

page 566 - get some friends and build a bridge together. Cross that stream you've always wanted to cross.

[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…