#algorithmic regulation

[mostlysignssomeportents]

Lies, damned lies, and Uber

I'm on tour with my new, nationally bestselling novel The Bezzle! Catch me TONIGHT in PHOENIX (Changing Hands, Feb 29) then Tucson (Mar 10-11), San Francisco (Mar 13), and more!

Uber lies about everything, especially money. Oh, and labour. Especially labour. And geometry. Especially geometry! But especially especially money. They constantly lie about money.

Uber are virtuosos of mendacity, but in Toronto, the company has attained a heretofore unseen hat-trick: they told a single lie that is dramatically, materially untruthful about money, labour and geometry! It's an achievement for the ages.

Here's how they did it.

For several decades, Toronto has been clobbered by the misrule of a series of far-right, clownish mayors. This was the result of former Ontario Premier Mike Harris's great gerrymander of 1998, when the city of Toronto was amalgamated with its car-dependent suburbs. This set the tone for the next quarter-century, as these outlying regions – utterly dependent on Toronto for core economic activity and massive subsidies to pay the unsustainable utility and infrastructure bills for sprawling neighborhoods of single-family homes – proceeded to gut the city they relied on.

These "conservative" mayors – the philanderer, the crackhead, the sexual predator – turned the city into a corporate playground, swapping public housing and rent controls for out-of-control real-estate speculation and trading out some of the world's best transit for total car-dependency. As part of that decay, the city rolled out the red carpet for Uber, allowing the company to put as many unlicensed taxis as they wanted on the city's streets.

Now, it's hard to overstate the dire traffic situation in Toronto. Years of neglect and underinvestment in both the roads and the transit system have left both in a state of near collapse and it's not uncommon for multiple, consecutive main arteries to shut down without notice for weeks, months, or, in a few cases, years. The proliferation of Ubers on the road – driven by desperate people trying to survive the city's cost-of-living catastrophe – has only exacerbated this problem.

Uber, of course, would dispute this. The company insists – despite all common sense and peer-reviewed research – that adding more cars to the streets alleviates traffic. This is easily disproved: there just isn't any way to swap buses, streetcars, and subways for cars. The road space needed for all those single-occupancy cars pushes everything further apart, which means we need more cars, which means more roads, which means more distance between things, and so on.

It is an undeniable fact that geometry hates cars. But geometry loathes Uber. Because Ubers have all the problems of single-occupancy vehicles, and then they have the separate problem that they just end up circling idly around the city's streets, waiting for a rider. The more Ubers there are on the road, the longer each car ends up waiting for a passenger:

https://www.sfgate.com/technology/article/Uber-Lyft-San-Francisco-pros-cons-ride-hailing-13841277.php

Anything that can't go on forever eventually stops. After years of bumbling-to-sinister municipal rule, Toronto finally reclaimed its political power and voted in a new mayor, Olivia Chow, a progressive of long tenure and great standing (I used to ring doorbells for her when she was campaigning for her city council seat). Mayor Chow announced that she was going to reclaim the city's prerogative to limit the number of Ubers on the road, ending the period of Uber's "self-regulation."

Uber, naturally, lost its shit. The company claims to be more than a (geometrically impossible) provider of convenient transportation for Torontonians, but also a provider of good jobs for working people. And to prove it, the company has promised to pay its drivers "120% of minimum wage." As I write for Ricochet, that's a whopper, even by Uber's standards:

https://ricochet.media/en/4039/uber-is-lying-again-the-company-has-no-intention-of-paying-drivers-a-living-wage

Here's the thing: Uber is only proposing to pay 120% of the minimum wage while drivers have a passenger in the vehicle. And with the number of vehicles Uber wants on the road, most drivers will be earning nothing most of the time. Factor in that unpaid time, as well as expenses for vehicles, and the average Toronto Uber driver stands to make $2.50 per hour (Canadian):

https://ridefair.ca/wp-content/uploads/2024/02/Legislated-Poverty.pdf

Now, Uber's told a lot of lies over the years. Right from the start, the company implicitly lied about what it cost to provide an Uber. For its first 12 years, Uber lost $0.41 on every dollar it brought in, lighting tens of billions in investment capital provided by the Saudi royals on fire in an effort to bankrupt rival transportation firms and disinvestment in municipal transit.

Uber then lied to retail investors about the business-case for buying its stock so that the House of Saud and other early investors could unload their stock. Uber claimed that they were on the verge of producing a self-driving car that would allow them to get rid of drivers, zero out their wage bill, and finally turn a profit. The company spent $2.5b on this, making it the most expensive Big Store in the history of cons:

https://www.theinformation.com/articles/infighting-busywork-missed-warnings-how-uber-wasted-2-5-billion-on-self-driving-cars

After years, Uber produced a "self-driving car" that could travel one half of one American mile before experiencing a potentially lethal collision. Uber quietly paid another company $400m to take this disaster off its hands:

https://www.economist.com/business/2020/12/10/why-is-uber-selling-its-autonomous-vehicle-division

The self-driving car lie was tied up in another lie – that somehow, automation could triumph over geometry. Robocabs, we were told, would travel in formations so tight that they would finally end the Red Queen's Race of more cars – more roads – more distance – more cars. That lie wormed its way into the company's IPO prospectus, which promised retail investors that profitability lay in replacing every journey – by car, cab, bike, bus, tram or train – with an Uber ride:

https://www.reuters.com/article/idUSKCN1RN2SK/

The company has been bleeding out money ever since – though you wouldn't know it by looking at its investor disclosures. Every quarter, Uber trumpets that it has finally become profitable, and every quarter, Hubert Horan dissects its balance sheets to find the accounting trick the company thought of this time. There was one quarter where Uber declared profitability by marking up the value of stock it held in Uber-like companies in other countries.

How did it get this stock? Well, Uber tried to run a business in those countries and it was such a total disaster that they had to flee the country, selling their business to a failing domestic competitor in exchange for stock in its collapsing business. Naturally, there's no market for this stock, which, in Uber-land, means you can assign any value you want to it. So that one quarter, Uber just asserted that the stock had shot up in value and voila, profit!

https://www.nakedcapitalism.com/2022/02/hubert-horan-can-uber-ever-deliver-part-twenty-nine-despite-massive-price-increases-uber-losses-top-31-billion.html

But all of those lies are as nothing to the whopper that Uber is trying to sell to Torontonians by blanketing the city in ads: the lie that by paying drivers $2.50/hour to fill the streets with more single-occupancy cars, they will turn a profit, reduce the city's traffic, and provide good jobs. Uber says it can vanquish geometry, economics and working poverty with the awesome power of narrative.

In other words, it's taking Toronto for a bunch of suckers.

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/2024/02/29/geometry-hates-uber/#toronto-the-gullible

Image: Rob Sinclair (modified) https://commons.wikimedia.org/wiki/File:Night_skyline_of_Toronto_May_2009.jpg

CC BY 2.0 https://creativecommons.org/licenses/by-sa/2.0/deed.en

[dad-friend]

ok listen. i know hbomberguy said he doesnt wanna become the type of youtube who spends their time doing drama videos or ruining ppl careers but like. if somebody doesnt start doing crazy detailed research on ryan hall, yall then i will

[aurosoulart]

some before-and-after pictures of how I’ve been using AI generated images in my art lately 🤖

I share other artists’ concerns about the unethical nature of the theft going on in the training data of AI art algorithms, so I refuse to spend any money on them or to consider the images generated by them to be true art, but I’m curious to hear people’s thoughts on using it for reference and paint-over like this?

my hope is that with proper regulation and more ethical use, AI could be a beneficial tool to help artists - instead of a way that allows people to steal from us more easily.

[chamiryokuroi]

There's no other alternatives. Most people don't like rping ocxcanon and not everyone can write or can afford commissions. Things have nuance and ai isn't inheritely bad. Chat bots have existed for years and that's all character ai is. A chat bot.

A chat bot as they have existed for decades has a set number of responses based on what you ask it, this set number of responses cannot be updated by the chatbot itself, instead whoever is the person responsible for the code would need to update the database of responses as well as the algorithm used to identify which response to give when asked a questions. That’s how chatbots work.

AI chatbot can and do update themselves based on the questions and responses you give them, that’s the main difference, and the creator can just filter out certain things if they do not want them (it has happened before with an AI where it taught itself to curse and the creator didn’t want that)

Now the problem here with RP is that you are most likely using characters under trademarks, characters from very popular franchises, and if at any point the creator of these AI bots decides to sell the content for profit they can go to the character owners and go “Hey here I have thousand of queries for X popular character of yours, filtering through them I can give you the 10x most popular asked questions, or the most used plotlines” and the character owner can go “oh this would be great to make a story based on the most popular questions!” and that’s how AI starts to fuck up with writers/authors.

[r0semultiverse]

I refuse to hop in a Zoox car in my entire life if I can avoid it. I refuse to hop into any self-driving robo taxi (or robotaxi) that uses AI to keep it’s passengers “safe.” If this is actually a service they are legally allowed to provide publicly, there’s about to be a whole bunch of new laws made in hopefully very little time! Now you know me, obviously fuck the law, many laws are unjust, but sometimes we need some regulations to keep up with the shit that rich Silicon Valley tech bros “put out” while claiming it’s allegedly their own work. These rich bastards are dangerous! Now I’ll pass along the questions that my partner & I jokingly pondered. If something happens that the AI & detection systems doesn’t know how to handle, will us as the passengers be held legally responsible say if a child gets punted into the air by the self driving car & we can’t do anything to stop it? What if we’re asleep assuming the car is safe & it runs over a legally endangered animal? What if we’re on our phones & these self-driving robot cars cleave someone in half? What if it crashes into someone’s private property? Are we held responsible in any of these cases or is the big rich guy’s company? If it’s anything like Tesla, you should get your kids or pets out of the road when you see a Zoox car coming, it could allegedly cause some mortalities. Two more things. What’s stopping someone from hijacking, hacking, or planting a virus on these self-driving taxi services? What if one of them gets hijacked to take someone to a human trafficker meetup spot? Will the company be held responsible at all? The gifs below pretty much summarizes my feelings.

[princesssarcastia]

listen to me. are you listening? tiktok is not uniquely anything when it comes to the internet. it is a tool and a platform like any other, used by all kinds of people—by nearly every kind of person or entity to whom it is available, in fact! and while what the u.s. government is doing right now to force the ownership of the company to change hands is bad and happening for the wrong reasons, to put it mildly—

claiming that the u.s. establishment is interested in shutting down tiktok because its been sooooo good and revolutionary for progressive/left-wing organizing is uhh. horse shit. that's not true. everyone uses tiktok. you, statistically, probably use tiktok. so do some of the congresspeople endorsing legislation that might end in tiktok being banned. so do right-wing influencers and terfs and trad-wives. just like everyone uses every other social media site.

don't fall into that trap of thinking that just because you and the people in your circle use this tool for good, that this tool is only used for good. it is actually just a tool for everyone!

here's an excerpt from a book called, The Wires of War, by Jacob Helberg which, if you're interested in why the u.s. congress is actually pulling this shit with tiktok, is a great read. this excerpt follows a section where Helberg described the role social media played in the Arab Spring in 2011. emphasis mine.

It would be several years before the 2016 election awakened the West to the ways in which the Internet could exploit the vulnerabilities of their societies. But for the autocrats in Bejing, Moscow, and Tehran, the Arab Spring was a technological awakening of their own. Seeing other repressive governments around the world crumble, illiberal regimes in Russia and China accelerated their treatment of the information space as a domain of war. "Tech-illiterate bureaucrats were replaced by a new generation of enforcers who understood the internet almost as well as the protesters," write Singer and Brooking in their book, LikeWar: The Weaponization of Social Media. "In truth, democratic activists had no special claim to the internet. They'd simply gotten there first. "

[spicyicymeloncat]

New zane concept. Since his emotions can be tampered with and changed, there is the possibility of him glitching or getting hacked and being super emotional. Like he’s actually just crying at everything, or being suddenly very grumpy and irritable, or overwhelmingly joyful.

What if also factors like food or sleep contribute to how glitchy he can be (mirroring humans), meaning a no sleep zane will be unusually grumpy.

Idk I really like the idea of zane getting an update that glitched his system and being unhinged until it’s fixed

[cancmbyn]

Christopher Nolan Warns of 'Terrifying Possibilities' as AI Reaches 'Oppenheimer Moment': 'We Have to Hold People Accountable'

By Kim J. Murphy

"I hope so," Nolan stated. "When I talk to the leading researchers in the field of AI right now, for example, they literally refer to this -- right now -- as their Oppenheimer moment. They're looking to history to say, 'What are the responsibilities for scientists developing new technologies that may have unintended consequences?'"

"Do you think Silicon Valley is thinking that right now?" Todd interjected. "Do you think they say that this is an Oppenheimer moment?"

"They say that they do," Nolan said after a pause and then chuckled. "It's helpful that that's in the conversation and I hope that that thought process will continue. I am not saying Oppenheimer's story offers any easy answers to those questions, but it at least can show where some of those responsibilities lie and how people take a breath and think, 'Okay, what is the accountability?'"

Accountability needs to come from external sources; If you look to Silicon Valley, it will never come wholly from within. There is no incentive to do so, when the profit-making incentive is the only one that really matters.

[panicinthestudio]

“TikTok Isn’t For Creators Anymore”, ICYMI Podcast, January 28, 2023

On today’s episode, Rachelle Hampton is joined by journalist and author Cory Doctorow to discuss his latest piece, “The Enshittification of TikTok,” in Wired. They talk about the life cycles of online platforms, why nobody on the platforms have any understanding of the rules of the game, and why we’re in dire need of better regulations. 

This podcast is produced by Daniel Schroeder, Rachelle Hampton, and Daisy Rosario.

Slate

[jcmarchi]

Regulating artificial intelligence: The bigger picture

New Post has been published on https://thedigitalinsider.com/regulating-artificial-intelligence-the-bigger-picture/

Regulating artificial intelligence: The bigger picture

Artificial intelligence: The impact of hype, economics and law

Artificial Intelligence (AI) continues to be a subject dominated by hype across the globe. According to McKinsey’s technology trends outlook 2024, 2023 saw $36 billion of equity investment in Generative Artificial Intelligence whereas $86 billion was invested in applied AI [1]. Currently, the UK AI market is worth in excess of £16.8 billion, with forecasted growth of over £801.6 billion by 2035 [2], reflecting the sizeable economic and technological traction AI is taking across sectors. 

Through the application of Computer Vision technology, for example, Marks and Spencer saw over 10 weeks an 80% reduction in warehouse accidents: just one of many ways in which AI is making a difference [3]. It however remains to be seen how effective coordinated governance will allow for innovation to thrive whilst maintaining cross-sector compliance.

Whilst the United Kingdom’s wider ambition is to be an AI Superpower, there has been continued debate and scrutiny about what constitutes effective AI regulation and how any continued iteration of such regulation would remain in alignment with key principles of law.

The United Kingdom’s vision for AI

The now-opposition government back in 2023 published its white paper, AI Regulation: A Pro-Innovation Approach. The plans outlined a principles-based approach to governance which was delegated to individual regulators.

While at the time it was thought that the UK’s approach and existing success in AI was down to effective regulator-led enforcement combined with technology-neutral legislation and regulations, the pace of AI highlighted gaps – both in opportunities and challenges – that would require addressing.

In the run-up to the 2024 UK General Election, regulation was of high importance in the Labour party’s manifesto under the “Kickstart economic growth” section, with the now-incumbent government seeking to strengthen AI regulation in specific areas. 

Keir Starmer – both prior to and post-election – emphasised the need for tougher approaches to AI regulation through, for example, the creation of a Regulatory Innovation Office (RIO) [4]. The aim of a Regulatory Innovation Office would, inter alia, set targets for technology regulators and monitor decision-making speed against core international benchmarks while providing guidance according to Labour’s higher-level industrial strategy. 

It, however, is not a new AI regulator and instead it will still be up to existing regulators to address AI within their specific fields. It is yet to be seen how a Regulatory Innovation Office would differ from the AI Safety Institute, the first state-backed organisation advancing AI safety established by the Conservative Government at the beginning of 2024 [5].

In addition to a new regulatory office, the planned creation of a National Data Library initiative aims to bring together existing research programmes and data-driven public services with strong safeguards and public benefit at its heart [4].

Wider issues in regulating AI

Government plans and economic potential aside, there are increasing expectations AI will solve the most pressing issues facing humanity. However, as a result of the pace there is a wider endemic issue of digital technologies challenging the functioning of law. In the long run, both a proportionate and future proof regulatory approach will be required regardless of where in the world approaches are developed.

To start with, defining AI is not straightforward: there is not a widely accepted definition, and considering various strands of sciences are affected either directly or indirectly by AI there is a risk of creating individualised definitions based on the specific field. Moreover, different types of intelligence could result in varying definitions of AI, even if the technological scope is not considered. 

Adding into the mixture the fields of Computer Science and Informatics – both not being directly mentioned in the AI Act, for example – demonstrates a lack of a commonly agreed technical definition of what AI is or could be. What follows from this are both general and theoretical questions and how this could be moulded into a legal definition. 

If, for example, both the principles of legal certainty and the protection of legitimate interests are taken, the existing definition of AI does not satisfy key requirements for legal definitions. The result instead is definitions that are ambiguous and debatable in practicability, creating a bottleneck in formulating domestic or even international AI regulation.

What is ultimately important is that any regulatory goal is aligned with the values of fundamental rights and the concrete protection of legal rights. Take the precautionary principle – an approach to risk management – which outlines that if a policy or action causes harm to the public and there is not a scientific agreement on the issue, that policy or action in question should not be carried out.

Applying this to AI becomes problematic as the effects in many cases are either not assessable just now or, in some cases, not at all. If then a risk assessment is carried out according to the proportionality principle – where the legality of an action is determined by the balance between the objective, means, and methods as well as the consequences of the action – where limited factual knowledge is obtainable, the actionability of such assessment becomes increasingly challenging.

Instead, it is the intersection of the technical functionality and the context of the application where a risk profile of an AI system can be obtained, but even then from a regulatory perspective these systems can vastly differ in risk profile.

Conclusion

The versatility of AI systems will present a range of opportunities and challenges depending on who uses them, what purposes they are used for and the resulting risk profiles. Attempting to regulate AI – which frankly speaking is an entire phenomenon with increasingly infinite branches of use cases – through a generalised Artificial Intelligence Act will not work.

Instead, deep-diving into the characteristics and the use cases of the differing algorithms and AI applications is more important and is strategically more likely to result in effective, iterative policymaking that is beneficial to society and innovation. 

Bibliography 

[1] McKinsey Tech Outlook 2024: www.mckinsey.com. (n.d.). McKinsey Technology Trends Outlook 2022 | McKinsey. [online] Available at: https://www.mckinsey.com/capabilities/mckinsey-digital/ our-insights/the-top-trends-in-tech#/. 

[2] AI Growth and Adoption: Hooson, M. (2024). UK Artificial Intelligence (AI) Statistics And Trends In 2024. [online] Forbes Advisor UK. Available at: https://www.forbes.com/uk/advisor/ business/software/uk-artificial-intelligence-ai-statistics-2024/. 

[3] M&S Computer Vision Example: Protex.ai. (2023). Marks and Spencer reduced incidents by 80% in their first 10 weeks of deployment. [online] Available at: https://www.protex.ai/case-studies/ marks-and-spencer#:~:text=This%20momentum%20led%20to%20an [Accessed 5 Sep. 2024]. 

[4] Labour Party Manifesto: The Labour Party. (2024). Kickstart economic growth – The Labour Party. [online] Available at: https://labour.org.uk/change/kickstart-economic-growth/#innovation [Accessed 30 Aug. 2024]. 

[5] AI Safety Institute: Aisi.gov.uk. (2024). The AI Safety Institute (AISI). [online] Available at: https://www.aisi.gov.uk [Accessed 30 Aug. 2024]. 

Interested in more from Ana? Make sure to give the articles below a read:

Ana Simion – AI Accelerator Institute

CEO @ INRO London | AI Advisory Council | Advisor in Artificial Intelligence | Keynote Speaker

[thisisgraeme]

Balancing AI Regulation in Education with Innovation: 6 Insights from Comparative Research

Curious about how AI is shaping the future of education? Our latest report dives into real-world insights from educators and AI experts. Discover the challenges, opportunities, and ethical considerations in AI integration.

As artificial intelligence (AI) becomes increasingly integral to educational practices, the debate over how to govern this powerful technology grows more pressing. The Organisation for Economic Co-operation and Development (OECD) recently published a working paper titled Artificial Intelligence and the Future of Work, Education, and Training, which delves into the potential impact of AI on equity…

[cozylittleartblog]

cant tell you how bad it feels to constantly tell other artists to come to tumblr, because its the last good website that isn't fucked up by spoonfeeding algorithms and AI bullshit and isn't based around meaningless likes

just to watch that all fall apart in the last year or so and especially the last two weeks

there's nowhere good to go anymore for artists.

edit - a lot of people are saying the tags are important so actually, you'll look at my tags.

#please dont delete your accounts because of the AI crap. your art deserves more than being lost like that #if you have a good PC please glaze or nightshade it. if you dont or it doesnt work with your style (like mine) please start watermarking #use a plain-ish font. make it your username. if people can't google what your watermark says and find ur account its not a good watermark #it needs to be central in the image - NOT on the canvas edges - and put it in multiple places if you are compelled #please dont stop posting your art because of this shit. we just have to hope regulations will come slamming down on these shitheads#in the next year or two and you want to have accounts to come back to. the world Needs real art #if we all leave that just makes more room for these scam artists to fill in with their soulless recycled garbage #improvise adapt overcome. it sucks but it is what it is for the moment. safeguard yourself as best you can without making #years of art from thousands of artists lost media. the digital world and art is too temporary to hastily click a Delete button out of spite

[mysticdragon3md3]

🌋💢->☮️🌻

View this post on Instagram

A post shared by Daniel Dueñas (@mrdanielduenas)

I was just journaling about how i need to learn how to do this. Maybe cookies in my computer are feeding my journaling to algorithms, but I'm glad this vid came across my feed. Because i genuinely need to learn how to express my dislike for characters without making their fans feel invalidated.

[buddyverse]

Can Africa Lead the Way? Decoding Bias and Building a Fairer AI Ecosystem

Mitigating bias in AI development, particularly through focusing on representative #African #data collection and fostering collaboration between African and Western #developers, will lead to a more equitable and inclusive future for #AI in Africa.

The rise of Artificial Intelligence (AI) has ignited a revolution across industries, from healthcare diagnostics to creative content generation. However, amidst the excitement lurks a shadow: bias. This insidious force can infiltrate AI systems, leading to discriminatory outcomes and perpetuating societal inequalities. As AI continues to integrate into the African landscape, the question of…

[hunter-rodrigez]

As sketchy as the oceangate submarine was... you can bet your ass every single one of musky's endeavors would look just as sketchy if it wasn't for the fact that he's forced to work with government regulators.

Hell, most of his projects are this sketchy if you look a bit closer. For example: the tesla tunnels.

No fire suppression system, no emergency exits, no emergency lighting, no way for EMS to get through, no fucking nothing. I am pretty sure it's not even big enough to open the car's doors.

Or the Cybertruck that's a deathtrap for both the people on the outside and the people on the inside because it utterly disregards the last 50 or so years of advancements in car safety technology such as crumple zones or safety glass

Or the tesla model 3 where you can't even open the back doors without power. So if you're in an accident and lose power... good luck getting your kids out of the back, especially when the huge battery is turning into a huge, unextinguishable flamethrower.

Or the fucking starship launchpad that was utterly destroyed by the rocket and threw huge concrete chunks and other debris around for miles... which, incidentally, also destroyed the rocket.

That's what all these self-proclaimed Silicon Valley tech bro geniuses are like.

They all think they know better than everyone else, and that rules or consequences don't apply to them, and they see safety as little more than an afterthought.

It's why Ai and social media algorithms are used sooooo ethically. It's why amazon and facebook try to find out everything about you and happily sell that data with no disregard for what it could be used for.

It's about damn time one of these CEO dipshits got killed by their own dipshitery, I just wish it had been musk or bezos instead...

Once again, in conclusion:

[govindhtech]

Tech Breakdown: What Is a SuperNIC? Get the Inside Scoop!

The most recent development in the rapidly evolving digital realm is generative AI. A relatively new phrase, SuperNIC, is one of the revolutionary inventions that makes it feasible.

Describe a SuperNIC

On order to accelerate hyperscale AI workloads on Ethernet-based clouds, a new family of network accelerators called SuperNIC was created. With remote direct memory access (RDMA) over converged Ethernet (RoCE) technology, it offers extremely rapid network connectivity for GPU-to-GPU communication, with throughputs of up to 400Gb/s.

SuperNICs incorporate the following special qualities:

Ensuring that data packets are received and processed in the same sequence as they were originally delivered through high-speed packet reordering. This keeps the data flow’s sequential integrity intact.

In order to regulate and prevent congestion in AI networks, advanced congestion management uses network-aware algorithms and real-time telemetry data.

In AI cloud data centers, programmable computation on the input/output (I/O) channel facilitates network architecture adaptation and extension.

Low-profile, power-efficient architecture that effectively handles AI workloads under power-constrained budgets.

Optimization for full-stack AI, encompassing system software, communication libraries, application frameworks, networking, computing, and storage.

Recently, NVIDIA revealed the first SuperNIC in the world designed specifically for AI computing, built on the BlueField-3 networking architecture. It is a component of the NVIDIA Spectrum-X platform, which allows for smooth integration with the Ethernet switch system Spectrum-4.

The NVIDIA Spectrum-4 switch system and BlueField-3 SuperNIC work together to provide an accelerated computing fabric that is optimized for AI applications. Spectrum-X outperforms conventional Ethernet settings by continuously delivering high levels of network efficiency.

Yael Shenhav, vice president of DPU and NIC products at NVIDIA, stated, “In a world where AI is driving the next wave of technological innovation, the BlueField-3 SuperNIC is a vital cog in the machinery.” “SuperNICs are essential components for enabling the future of AI computing because they guarantee that your AI workloads are executed with efficiency and speed.”

The Changing Environment of Networking and AI

Large language models and generative AI are causing a seismic change in the area of artificial intelligence. These potent technologies have opened up new avenues and made it possible for computers to perform new functions.

GPU-accelerated computing plays a critical role in the development of AI by processing massive amounts of data, training huge AI models, and enabling real-time inference. While this increased computing capacity has created opportunities, Ethernet cloud networks have also been put to the test.

The internet’s foundational technology, traditional Ethernet, was designed to link loosely connected applications and provide wide compatibility. The complex computational requirements of contemporary AI workloads, which include quickly transferring large amounts of data, closely linked parallel processing, and unusual communication patterns all of which call for optimal network connectivity were not intended for it.

Basic network interface cards (NICs) were created with interoperability, universal data transfer, and general-purpose computing in mind. They were never intended to handle the special difficulties brought on by the high processing demands of AI applications.

The necessary characteristics and capabilities for effective data transmission, low latency, and the predictable performance required for AI activities are absent from standard NICs. In contrast, SuperNICs are designed specifically for contemporary AI workloads.

Benefits of SuperNICs in AI Computing Environments

Data processing units (DPUs) are capable of high throughput, low latency network connectivity, and many other sophisticated characteristics. DPUs have become more and more common in the field of cloud computing since its launch in 2020, mostly because of their ability to separate, speed up, and offload computation from data center hardware.

SuperNICs and DPUs both have many characteristics and functions in common, however SuperNICs are specially designed to speed up networks for artificial intelligence.

The performance of distributed AI training and inference communication flows is highly dependent on the availability of network capacity. Known for their elegant designs, SuperNICs scale better than DPUs and may provide an astounding 400Gb/s of network bandwidth per GPU.

When GPUs and SuperNICs are matched 1:1 in a system, AI workload efficiency may be greatly increased, resulting in higher productivity and better business outcomes.

SuperNICs are only intended to speed up networking for cloud computing with artificial intelligence. As a result, it uses less processing power than a DPU, which needs a lot of processing power to offload programs from a host CPU.

Less power usage results from the decreased computation needs, which is especially important in systems with up to eight SuperNICs.

One of the SuperNIC’s other unique selling points is its specialized AI networking capabilities. It provides optimal congestion control, adaptive routing, and out-of-order packet handling when tightly connected with an AI-optimized NVIDIA Spectrum-4 switch. Ethernet AI cloud settings are accelerated by these cutting-edge technologies.

Transforming cloud computing with AI

The NVIDIA BlueField-3 SuperNIC is essential for AI-ready infrastructure because of its many advantages.

Maximum efficiency for AI workloads: The BlueField-3 SuperNIC is perfect for AI workloads since it was designed specifically for network-intensive, massively parallel computing. It guarantees bottleneck-free, efficient operation of AI activities.

Performance that is consistent and predictable: The BlueField-3 SuperNIC makes sure that each job and tenant in multi-tenant data centers, where many jobs are executed concurrently, is isolated, predictable, and unaffected by other network operations.

Secure multi-tenant cloud infrastructure: Data centers that handle sensitive data place a high premium on security. High security levels are maintained by the BlueField-3 SuperNIC, allowing different tenants to cohabit with separate data and processing.

Broad network infrastructure: The BlueField-3 SuperNIC is very versatile and can be easily adjusted to meet a wide range of different network infrastructure requirements.

Wide compatibility with server manufacturers: The BlueField-3 SuperNIC integrates easily with the majority of enterprise-class servers without using an excessive amount of power in data centers.