#nvidia income

[reportwire]

Nvidia CEO praises ‘through the roof’ use of firm’s A.I. services—and investors seem to agree

Nvidia shares jumped in after-hours trading Wednesday, as the chipmaker beat expectations on revenue and said it was benefitting from a growing boom inA.I. technology driven by chatbots like OpenAI’s ChatGPT. The U.S.-based chip company’s revenues fell, as it reported $6.1 billion in revenue in the most recent quarter, a 21% fall from what it reported a year ago. (That revenue, at $7.6 billion,…

[kc22invesmentsblog]

The AI Revolution: Exploring AI Stocks and Their Potential for the Future

Written by Delvin Artificial Intelligence (AI) has emerged as a transformative force, revolutionizing industries and shaping the future of technology. As AI continues to gain momentum, investing in AI stocks presents an opportunity to participate in this technological revolution and potentially reap significant benefits. In this blog post, we will discuss the impact of AI on the future and delve…

[mostlysignssomeportents]

“Humans in the loop” must detect the hardest-to-spot errors, at superhuman speed

I'm touring my new, nationally bestselling novel The Bezzle! Catch me SATURDAY (Apr 27) in MARIN COUNTY, then Winnipeg (May 2), Calgary (May 3), Vancouver (May 4), and beyond!

If AI has a future (a big if), it will have to be economically viable. An industry can't spend 1,700% more on Nvidia chips than it earns indefinitely – not even with Nvidia being a principle investor in its largest customers:

https://news.ycombinator.com/item?id=39883571

A company that pays 0.36-1 cents/query for electricity and (scarce, fresh) water can't indefinitely give those queries away by the millions to people who are expected to revise those queries dozens of times before eliciting the perfect botshit rendition of "instructions for removing a grilled cheese sandwich from a VCR in the style of the King James Bible":

https://www.semianalysis.com/p/the-inference-cost-of-search-disruption

Eventually, the industry will have to uncover some mix of applications that will cover its operating costs, if only to keep the lights on in the face of investor disillusionment (this isn't optional – investor disillusionment is an inevitable part of every bubble).

Now, there are lots of low-stakes applications for AI that can run just fine on the current AI technology, despite its many – and seemingly inescapable - errors ("hallucinations"). People who use AI to generate illustrations of their D&D characters engaged in epic adventures from their previous gaming session don't care about the odd extra finger. If the chatbot powering a tourist's automatic text-to-translation-to-speech phone tool gets a few words wrong, it's still much better than the alternative of speaking slowly and loudly in your own language while making emphatic hand-gestures.

There are lots of these applications, and many of the people who benefit from them would doubtless pay something for them. The problem – from an AI company's perspective – is that these aren't just low-stakes, they're also low-value. Their users would pay something for them, but not very much.

For AI to keep its servers on through the coming trough of disillusionment, it will have to locate high-value applications, too. Economically speaking, the function of low-value applications is to soak up excess capacity and produce value at the margins after the high-value applications pay the bills. Low-value applications are a side-dish, like the coach seats on an airplane whose total operating expenses are paid by the business class passengers up front. Without the principle income from high-value applications, the servers shut down, and the low-value applications disappear:

https://locusmag.com/2023/12/commentary-cory-doctorow-what-kind-of-bubble-is-ai/

Now, there are lots of high-value applications the AI industry has identified for its products. Broadly speaking, these high-value applications share the same problem: they are all high-stakes, which means they are very sensitive to errors. Mistakes made by apps that produce code, drive cars, or identify cancerous masses on chest X-rays are extremely consequential.

Some businesses may be insensitive to those consequences. Air Canada replaced its human customer service staff with chatbots that just lied to passengers, stealing hundreds of dollars from them in the process. But the process for getting your money back after you are defrauded by Air Canada's chatbot is so onerous that only one passenger has bothered to go through it, spending ten weeks exhausting all of Air Canada's internal review mechanisms before fighting his case for weeks more at the regulator:

https://bc.ctvnews.ca/air-canada-s-chatbot-gave-a-b-c-man-the-wrong-information-now-the-airline-has-to-pay-for-the-mistake-1.6769454

There's never just one ant. If this guy was defrauded by an AC chatbot, so were hundreds or thousands of other fliers. Air Canada doesn't have to pay them back. Air Canada is tacitly asserting that, as the country's flagship carrier and near-monopolist, it is too big to fail and too big to jail, which means it's too big to care.

Air Canada shows that for some business customers, AI doesn't need to be able to do a worker's job in order to be a smart purchase: a chatbot can replace a worker, fail to their worker's job, and still save the company money on balance.

I can't predict whether the world's sociopathic monopolists are numerous and powerful enough to keep the lights on for AI companies through leases for automation systems that let them commit consequence-free free fraud by replacing workers with chatbots that serve as moral crumple-zones for furious customers:

https://www.sciencedirect.com/science/article/abs/pii/S0747563219304029

But even stipulating that this is sufficient, it's intrinsically unstable. Anything that can't go on forever eventually stops, and the mass replacement of humans with high-speed fraud software seems likely to stoke the already blazing furnace of modern antitrust:

https://www.eff.org/de/deeplinks/2021/08/party-its-1979-og-antitrust-back-baby

Of course, the AI companies have their own answer to this conundrum. A high-stakes/high-value customer can still fire workers and replace them with AI – they just need to hire fewer, cheaper workers to supervise the AI and monitor it for "hallucinations." This is called the "human in the loop" solution.

The human in the loop story has some glaring holes. From a worker's perspective, serving as the human in the loop in a scheme that cuts wage bills through AI is a nightmare – the worst possible kind of automation.

Let's pause for a little detour through automation theory here. Automation can augment a worker. We can call this a "centaur" – the worker offloads a repetitive task, or one that requires a high degree of vigilance, or (worst of all) both. They're a human head on a robot body (hence "centaur"). Think of the sensor/vision system in your car that beeps if you activate your turn-signal while a car is in your blind spot. You're in charge, but you're getting a second opinion from the robot.

Likewise, consider an AI tool that double-checks a radiologist's diagnosis of your chest X-ray and suggests a second look when its assessment doesn't match the radiologist's. Again, the human is in charge, but the robot is serving as a backstop and helpmeet, using its inexhaustible robotic vigilance to augment human skill.

That's centaurs. They're the good automation. Then there's the bad automation: the reverse-centaur, when the human is used to augment the robot.

Amazon warehouse pickers stand in one place while robotic shelving units trundle up to them at speed; then, the haptic bracelets shackled around their wrists buzz at them, directing them pick up specific items and move them to a basket, while a third automation system penalizes them for taking toilet breaks or even just walking around and shaking out their limbs to avoid a repetitive strain injury. This is a robotic head using a human body – and destroying it in the process.

An AI-assisted radiologist processes fewer chest X-rays every day, costing their employer more, on top of the cost of the AI. That's not what AI companies are selling. They're offering hospitals the power to create reverse centaurs: radiologist-assisted AIs. That's what "human in the loop" means.

This is a problem for workers, but it's also a problem for their bosses (assuming those bosses actually care about correcting AI hallucinations, rather than providing a figleaf that lets them commit fraud or kill people and shift the blame to an unpunishable AI).

Humans are good at a lot of things, but they're not good at eternal, perfect vigilance. Writing code is hard, but performing code-review (where you check someone else's code for errors) is much harder – and it gets even harder if the code you're reviewing is usually fine, because this requires that you maintain your vigilance for something that only occurs at rare and unpredictable intervals:

https://twitter.com/qntm/status/1773779967521780169

But for a coding shop to make the cost of an AI pencil out, the human in the loop needs to be able to process a lot of AI-generated code. Replacing a human with an AI doesn't produce any savings if you need to hire two more humans to take turns doing close reads of the AI's code.

This is the fatal flaw in robo-taxi schemes. The "human in the loop" who is supposed to keep the murderbot from smashing into other cars, steering into oncoming traffic, or running down pedestrians isn't a driver, they're a driving instructor. This is a much harder job than being a driver, even when the student driver you're monitoring is a human, making human mistakes at human speed. It's even harder when the student driver is a robot, making errors at computer speed:

https://pluralistic.net/2024/04/01/human-in-the-loop/#monkey-in-the-middle

This is why the doomed robo-taxi company Cruise had to deploy 1.5 skilled, high-paid human monitors to oversee each of its murderbots, while traditional taxis operate at a fraction of the cost with a single, precaratized, low-paid human driver:

https://pluralistic.net/2024/01/11/robots-stole-my-jerb/#computer-says-no

The vigilance problem is pretty fatal for the human-in-the-loop gambit, but there's another problem that is, if anything, even more fatal: the kinds of errors that AIs make.

Foundationally, AI is applied statistics. An AI company trains its AI by feeding it a lot of data about the real world. The program processes this data, looking for statistical correlations in that data, and makes a model of the world based on those correlations. A chatbot is a next-word-guessing program, and an AI "art" generator is a next-pixel-guessing program. They're drawing on billions of documents to find the most statistically likely way of finishing a sentence or a line of pixels in a bitmap:

https://dl.acm.org/doi/10.1145/3442188.3445922

This means that AI doesn't just make errors – it makes subtle errors, the kinds of errors that are the hardest for a human in the loop to spot, because they are the most statistically probable ways of being wrong. Sure, we notice the gross errors in AI output, like confidently claiming that a living human is dead:

https://www.tomsguide.com/opinion/according-to-chatgpt-im-dead

But the most common errors that AIs make are the ones we don't notice, because they're perfectly camouflaged as the truth. Think of the recurring AI programming error that inserts a call to a nonexistent library called "huggingface-cli," which is what the library would be called if developers reliably followed naming conventions. But due to a human inconsistency, the real library has a slightly different name. The fact that AIs repeatedly inserted references to the nonexistent library opened up a vulnerability – a security researcher created a (inert) malicious library with that name and tricked numerous companies into compiling it into their code because their human reviewers missed the chatbot's (statistically indistinguishable from the the truth) lie:

https://www.theregister.com/2024/03/28/ai_bots_hallucinate_software_packages/

For a driving instructor or a code reviewer overseeing a human subject, the majority of errors are comparatively easy to spot, because they're the kinds of errors that lead to inconsistent library naming – places where a human behaved erratically or irregularly. But when reality is irregular or erratic, the AI will make errors by presuming that things are statistically normal.

These are the hardest kinds of errors to spot. They couldn't be harder for a human to detect if they were specifically designed to go undetected. The human in the loop isn't just being asked to spot mistakes – they're being actively deceived. The AI isn't merely wrong, it's constructing a subtle "what's wrong with this picture"-style puzzle. Not just one such puzzle, either: millions of them, at speed, which must be solved by the human in the loop, who must remain perfectly vigilant for things that are, by definition, almost totally unnoticeable.

This is a special new torment for reverse centaurs – and a significant problem for AI companies hoping to accumulate and keep enough high-value, high-stakes customers on their books to weather the coming trough of disillusionment.

This is pretty grim, but it gets grimmer. AI companies have argued that they have a third line of business, a way to make money for their customers beyond automation's gifts to their payrolls: they claim that they can perform difficult scientific tasks at superhuman speed, producing billion-dollar insights (new materials, new drugs, new proteins) at unimaginable speed.

However, these claims – credulously amplified by the non-technical press – keep on shattering when they are tested by experts who understand the esoteric domains in which AI is said to have an unbeatable advantage. For example, Google claimed that its Deepmind AI had discovered "millions of new materials," "equivalent to nearly 800 years’ worth of knowledge," constituting "an order-of-magnitude expansion in stable materials known to humanity":

https://deepmind.google/discover/blog/millions-of-new-materials-discovered-with-deep-learning/

It was a hoax. When independent material scientists reviewed representative samples of these "new materials," they concluded that "no new materials have been discovered" and that not one of these materials was "credible, useful and novel":

https://www.404media.co/google-says-it-discovered-millions-of-new-materials-with-ai-human-researchers/

As Brian Merchant writes, AI claims are eerily similar to "smoke and mirrors" – the dazzling reality-distortion field thrown up by 17th century magic lantern technology, which millions of people ascribed wild capabilities to, thanks to the outlandish claims of the technology's promoters:

https://www.bloodinthemachine.com/p/ai-really-is-smoke-and-mirrors

The fact that we have a four-hundred-year-old name for this phenomenon, and yet we're still falling prey to it is frankly a little depressing. And, unlucky for us, it turns out that AI therapybots can't help us with this – rather, they're apt to literally convince us to kill ourselves:

https://www.vice.com/en/article/pkadgm/man-dies-by-suicide-after-talking-with-ai-chatbot-widow-says

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/2024/04/23/maximal-plausibility/#reverse-centaurs

Image: Cryteria (modified) https://commons.wikimedia.org/wiki/File:HAL9000.svg

CC BY 3.0 https://creativecommons.org/licenses/by/3.0/deed.en

[datarep]

NVIDIA Income Statement Q1 FY2025

by u/giteam

[lyingbard]

Update: Patience Fans Winning Again (Import Poll Decisions Too!)

So I've got a version working with all the features for a solid beta, but... only on my computer.

It should work when I set it up with all the cloud nonsense it needs, but it costs money, I don't wanna spend money right now, and I can't really make you pay for a product I'm not sure will work right.

So here's the deal: I'm starting a paid internship soon, so once I have that income I'll be willing to spend money on this. Problem: it's a National Parks internship so I won't have internet or the computer that I make LyingBard with until I get back... in 3-6 months.

But! I also want to ask you an important question...

I've been making LyingBard as a Cloud-Based app. It allows you to use it from anywhere through my website, but it also means I incur the cost of finding GPUs to run this with while you have a perfectly good GPU sitting in your computer doing nothing (also cloud apps are a pain in the ass).

I could also make it a Desktop App, but it would be about 1GB (blame PyTorch), it would only run on NVIDIA GPUs, and you'd have to set up your own discord bots and stuff (although I can try and streamline that for you).

Another big problem is money. Cloud-Based stuff costs money to run and becomes basically a job even if it doesn't pay enough. I'm considering a career in the National Parks Service so I won't be available most of the time if something goes wrong and stuff can go VERY wrong with a paid cloud app (think leaked passwords, compromised payment processor (Stripe) account, that sort of thing).

A Desktop App, however, can be left alone without spontaneously deleting itself or attacking you, but I would certainly have to focus on a career unless you donated a whole heck of a lot.

So DECIDE TIME! After carefully (or carelessly, idc) considering these options. WHICH DO YOU CHOOSE?!

Unfortunately, LyingBard isn't releasing until I get back regardless. Even the desktop app is just a bit too much work for me to get done before I leave.

[sideburnguru]

My hot take on the AI vs creativity debate. For context I'm a filmmaker and mess around with all creative aspects of bringing something to the screen.

It's the same argument with automation. Growing up in the 2010's you couldn't go long without being asked to consider whether robots replacing human jobs was ethical or not. Short answer was no, since it's replacing unskilled labour and would lead to millions of people around the world losing their income. But back then the jobs in question were specifically unskilled labour, something NON INTELLIGENT.

The first wave of AI being creative as I remember it was the shitty generation of landscapes and around 2020 ish. Same thing as today where it would create images based off of prompts, but it was really shitty and would only barely resemble what you had in mind, and couldn't even do anything specific. It was closer to a gimmick than anything.

The second wave in my memory was when Nvidia and a bunch of companies made software that could generate landscapes based off of prompts or some unique software with brushes and stuff. The stuff was, all things considered, usable and decent looking.

And the third wave is what happened as soon as chatGPT came into existence, and the modern debate. The weird thing is that (as far as I remember) people weren't raising hell during the first two waves. It was only until after the art became good and the technology became able to understand more advanced prompts did we complain. We recycled the arguments from automation because it was essentially the same thing, but now there was an argument that AI art has "no soul".

That last argument really stands out, because I genuinely don't believe a majority of people have what I consider a soul, not even creatives. I think it's something that has to by the individual through discovering and defining their meaning of life. Yet, even the soulless are asking for AI to be limited or stopped being developed because it may stifle their creativity or employment prospects.

How I see it? Knowing that it could very well prevent me from being able to make a living from doing the thing I've decided to dedicate my life to? I say bring it on. I think this is the defining struggle of creatives of our generation, to be able to prove their worth against frankly superior soulless artists.

Want to be employed for being creative? If you can't beat AI then you probably weren't going to make it too far anyways.

Want to express creativity for yourself? No one's stopping you, create your magnum opus.

I know about AI being trained on existing artists art and how it's going to just further the evil capitalist machine but as it is this is where I stand.

[govindhtech]

NVIDIA AI Aerial Upgrades Wireless AI-RAN With Generative AI

NVIDIA AI Aerial Optimizes Wireless Networks, Delivers Next-Generation AI Experiences on One Platform

With an AI computing infrastructure, telecommunications companies are moving beyond voice and data services to optimize wireless networks and meet the demands of generative AI on mobile, robotics, autonomous vehicles, smart factories, 5G, and many other areas.

A set of accelerated computing hardware and software called NVIDIA AI Aerial was unveiled today with the goal of developing, modeling, training, and implementing AI radio access network technology (AI-RAN) for wireless networks in the AI age.

The platform will develop into an essential building block that enables large-scale network optimization to meet the needs of numerous new services. As a result, there will be large total cost of ownership savings and new income streams for enterprise and consumer services for telecom providers.

Telecommunications service providers can now support generative AI-driven co-pilots and personal assistants, teleoperations for manufacturing robots and autonomous vehicles, computer vision in manufacturing and agriculture, logistics, emerging spatial computing applications, robotic surgery, 3D collaboration, and 5G and 6G advancements thanks to NVIDIA AI Aerial.

AI-RAN

Driving Future Networks With AI-RAN

The first AI-RAN platform in the world, NVIDIA AI Aerial, can host generative AI, manage RAN traffic, and incorporate AI into network optimization.

With edge AI apps to host internal and external generative AI applications, AI-RAN provides software-defined RAN that is both high-performance and energy-efficient. It also improves network experience and opens up new revenue streams.

The multifunctional networks of the future that depend on AI-powered telecommunications capabilities are built on AI-RAN.

Using NVIDIA AI Aerial in the Telecom Sector

In order to enable telecom operators to engage at any point from development to deployment for next-generation wireless networks, the NVIDIA AI Aerial platform provides access to a full range of capabilities, including a high-performance, software-defined RAN along with training, modeling, and inference options.

Among the features of the NVIDIA AI Aerial platform are:

Software libraries are included in NVIDIA Aerial CUDA-Accelerated RAN to help partners create and implement high-performance virtualized RAN workloads on computing platforms that are accelerated by NVIDIA.

The PyTorch and TensorFlow software libraries included in the NVIDIA Aerial AI Radio Frameworks are used to create and train models that enhance spectral efficiency and introduce new functionalities to the processing of 5G and 6G radio signals. NVIDIA Sionna, a link-level simulator that facilitates the creation and training of neural network-based 5G and 6G radio algorithms, is also included in this.

A framework for developing network digital twins at the system level is called NVIDIA Aerial Omniverse Digital Twin (AODT). With the use of AODT, wireless networks can be simulated with physical accuracy, ranging from a single base station to a vast network with numerous base stations spanning a whole city. It includes realistic terrain and object attributes of the actual world, user-equipment simulators, and software-defined RAN (Aerial-CUDA Accelerated RAN).

NVIDIA Innovation Center for AI Aerial and AI RAN

With the launch of the AI-RAN Innovation Center, NVIDIA is working with T-Mobile, Ericsson, and Nokia to quicken the commercialization of AI-RAN.

The facility will make use of the NVIDIA AI Aerial platform’s primary features. Through the development of AI-RAN, the partnership aims to bring RAN and AI innovation closer together to give customers’ revolutionary network experiences.

Ericsson’s investment in its AI-RAN technology, communications service providers may now implement portable RAN software that works on a variety of platforms.

The NVIDIA AI Aerial Environment

Softbank and Fujitsu are important members of the NVIDIA AI Aerial ecosystem.

For testing and simulation purposes, Ansys and Keysight use the NVIDIA Aerial Omniverse Digital Twin, and academic partners including Deepsig, ETH-Zurich, Northeastern University, and Samsung work together on 6G research and NVIDIA Aerial AI Radio Frameworks.

Key partners for NVIDIA AI Aerial include cloud stack software companies like Aarna Networks, Canonical, Red Hat, and Wind River; networking stack providers like Arrcus network; and server infrastructure providers like Dell Technologies, Hewlett Packard Enterprise, and Supermicro. AI solution decision-making is speeding up with the help of edge solution providers like Vapor.io and system integrators like World Wide Technology and its AI Proving Ground.

Read more on govindhtech.com

[willknowledge]

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https://www.youtube.com/watch?v=dJfOa5wz8yQ HUGE SELL ON WARREN BUFFET STOCK! INCOMING CRASH⁉️ KNOW THIS! #shorts #stockmarket #stocks SEE MY BUYS AND SELLS! ALSO JOIN PRIVATE TRADING STREAMS! 👉 Website: https://ift.tt/r5ijJ4Q ✅ Subscribe To My Channel For More Videos: https://www.youtube.com/@WillKnowledge/?sub_confirmation=1 ✅ Important Links: Use my same platform (Trading view) To have the exact same levels! 👉 https://ift.tt/nuXW4gY This is an affiliate code, I will receive compensation from you signing up! 👉 Website: https://ift.tt/r5ijJ4Q ✅ Stay Connected With Me: 👉 Instagram: https://ift.tt/M7sIo6J ============================== ✅ Other Videos You Might Be Interested In Watching: 👉 Double Your Money in 2 Minutes! Stock Market Tips to Turn $1,000 into $1,000 | Will Knowledge https://www.youtube.com/watch?v=Qrw_a6EuHtg 👉 Best Stocks to Buy Now: NVIDIA, Tesla, Nike, Meta, Gold, and More! | Will Knowledge https://www.youtube.com/watch?v=6jl_siqD09A 👉 Stock Market Crash Alert: Key Levels You Must Watch! | Will Knowledge https://www.youtube.com/watch?v=JLsh_-HZoOE 👉 Top Buys: Tesla, Nvidia, AMC, Apple, and More Stock Market Analysis! | Will Knowledge https://www.youtube.com/watch?v=PTM98qWBfd8 ============================= ✅ About Will Knowledge: Hello Team! This channel is about investing in the stock market, trading options, and general knowledge of the market tools to use to your benefit so we can all spread the wealth. For collaboration and business inquiries, please use the contact information below: 📩 Email: willknowledge77@gmail.com 🔔 Subscribe to my channel for more videos: https://www.youtube.com/@WillKnowledge/?sub_confirmation=1 ===================== #warrenbuffet #biden #trump Disclaimer: These videos are for educational and entertainment purposes only and should not be construed as financial advice or a recommendation to buy or sell any security or investment. I am not a financial advisor, and the information provided is not intended as investment recommendations. Please consult with a licensed financial professional before making any financial decisions. I shall not be held liable for any losses incurred from investing or trading in the stock market, including attempts to mirror my actions. Remember, unless investments are FDIC insured, they may decline in value and/or disappear entirely. Copyright Disclaimer: Under Section 107 of the Copyright Act 1976, allowance is made for "fair use" for purposes such as criticism, comment, news reporting, teaching, scholarship and research. Fair use is a use permitted by copyright statute that might otherwise be infringing. Non-profit, educational or personal use tips the balance in favor of fair use © Will Knowledge via Will Knowledge https://www.youtube.com/channel/UCXnjHTVPeCp7hNEj_15Gx4w September 16, 2024 at 11:32PM

[usnewsrank]

Schroder Oriental Income Fund – capturing the artificial intelligence opportunity in Asia

  Harnessing the potential of Asia’s technology leaders   Artificial intelligence (AI) has become a major force in global stock markets, driving significant returns over the past couple of years. Although much of the attention has focused on Nvidia, the US technology company that designs the advanced chips which are essential for AI processing, there is a robust ecosystem of other technology…

[jcmarchi]

Amazon partners with Anthropic to enhance Alexa

New Post has been published on https://thedigitalinsider.com/amazon-partners-with-anthropic-to-enhance-alexa/

Amazon partners with Anthropic to enhance Alexa

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Amazon is gearing up to roll out a revamped version of its Alexa voice assistant, which is expected to be available this October, right before the US shopping rush.

Internally referred to as “Remarkable,” the new technology will be powered by Anthropic’s Claude AI models. Sources close to the matter have indicated that this shift occurred due to the underperformance of Amazon’s in-house software.

The enhanced Alexa will operate using advanced generative AI to handle more complex queries. Amazon plans to offer the new Alexa as a subscription service, priced between $5 and $10 per month, while the classic version of Alexa will remain free. This approach marks a significant change for Amazon and suggests that the company aims to turn this voice assistant into a profitable venture after years of limited success in generating revenue through this platform.

Amazon’s decision to quickly adopt an external model, Claude, indicates a strategic shift. Amazon typically prefers to build everything in-house to minimise its dependence on third-party vendors, thereby avoiding external influences on customer behaviour and business strategies, as well as external influences on who controls data. However, it seems that Amazon’s traditional strategy does not provide the massive AI capability needed, or perhaps Amazon has realised the need for more powerful AI. It is also worth noting that the involved AI developer, OpenAI, is affiliated with major technology companies like Apple and Microsoft in developing AI technologies.

The launch of the “Remarkable” Alexa is anticipated during Amazon’s annual devices and services event in September, though the company has not confirmed the exact date. This event will also mark the first public appearance of Panos Panay, the new head of Amazon’s devices division, who has taken over from long-time executive David Limp.

The updated version of Alexa would be a more interactive and intuitive assistant, as the new functionality would stem from its conversational mode. The assistant is envisioned to do more than just recognise patterns in people’s speech; it would be able to hold conversations built on previous interactions. The most likely features include personalised shopping advice, news aggregation, and more advanced home automation. As for whether customers would pay for Alexa, this likely depends on the final set of available features. The issue might be particularly pressing for Amazon, given that customers already pay for Prime membership.

The future for Alexa is quite ambitious, but it also bears significant risks. For the new version to be successful, internal performance benchmarks must be met. While estimates for “Remarkable” Alexa suggest that even a small percentage of current users paying for the premium version could become a substantial income stream for Amazon, the likelihood of achieving the expected outcomes remains uncertain.

However, Amazon’s partnership with Anthropic is currently under regulatory review, largely due to an investigation by the UK’s antitrust regulator. The impending upgrade announcement and the regulator’s response could significantly influence the company’s future activities.

Amazon’s initiative to adopt an AI solution developed by Anthropic marks a significant shift for the company, which previously focused on developing its proprietary technology. At this point, it is possible to view this move as part of the general trend in the industry to turn to partnerships regarding AI development to enhance the competitiveness of products.

See also: Amazon strives to outpace Nvidia with cheaper, faster AI chips

Want to learn more about AI and big data from industry leaders? Check out AI & Big Data Expo taking place in Amsterdam, California, and London. The comprehensive event is co-located with other leading events including Intelligent Automation Conference, BlockX, Digital Transformation Week, and Cyber Security & Cloud Expo.

Explore other upcoming enterprise technology events and webinars powered by TechForge here.

Tags: ai, alexa, Amazon, artificial intelligence, claude, generative ai, voice assistant

[recentlyheardcom]

Nvidia stock slips even after earnings top Wall Street estimates and demand for AI chips surges | National News

LOS ANGELES (AP) — Nvidia may have exceeded Wall Street estimates as its profit jumped — buffeted by the chipmaking dominance that has cemented Nvidia’s place as the poster child of the artificial intelligence boom — but investors seemed less than impressed. The company reported a net income of to $16.6 billion. Adjusted for one-time items, net income was $16.95 billion. Revenue rose to $30…

[shubhampawrainfinium]

Streaming Media Devices: Powering the Future of Home Entertainment and Digital Content Consumption

Market Overview and Report Coverage

The streaming media device market has seen exponential growth in recent years, driven by the increasing consumer demand for on-demand content, the rapid proliferation of high-speed internet, and the shift from traditional cable TV to streaming services. Streaming media devices, including smart TVs, streaming sticks, set-top boxes, and gaming consoles, enable users to access content from platforms like Netflix, Hulu, Amazon Prime, and YouTube directly on their televisions or other display devices.

According to Infinium Global Research, the global streaming media device market is expected to grow significantly from 2023 to 2030. This growth is fueled by the rising adoption of Over-The-Top (OTT) services, advancements in streaming technology, and the growing trend of cord-cutting, where consumers cancel their cable or satellite TV subscriptions in favor of streaming services. Additionally, the increasing integration of voice control and AI-driven recommendation systems into streaming devices is further enhancing the user experience and driving market demand.

Market Segmentation

By Type:

Smart TVs: Smart TVs have built-in internet connectivity and streaming apps, making them a popular choice for consumers who want an all-in-one solution for accessing streaming content. The demand for 4K and 8K resolution smart TVs is growing, driven by advancements in display technology and increasing availability of high-definition content.

Streaming Sticks and Dongles: Devices like Amazon Fire Stick, Google Chromecast, and Roku are popular for their affordability and ease of use. These compact devices can be plugged into any TV with an HDMI port, transforming it into a smart TV capable of streaming content from various platforms.

Set-Top Boxes: Set-top boxes, such as Apple TV and Nvidia Shield, offer more advanced features than streaming sticks, including higher storage capacity, better processing power, and support for gaming and smart home integration. They are ideal for consumers looking for a premium streaming experience.

Gaming Consoles: Gaming consoles like Xbox and PlayStation double as streaming devices, offering access to popular streaming apps alongside gaming. The multifunctionality of these devices makes them a popular choice among gamers who also consume streaming content.

By Application:

Residential: The residential segment dominates the streaming media device market, with millions of households worldwide using these devices to access on-demand entertainment. The convenience, variety of content, and cost-effectiveness of streaming services compared to traditional cable TV are key factors driving adoption in this segment.

Commercial: In the commercial sector, streaming media devices are increasingly being used in hotels, restaurants, and bars to offer entertainment to customers. Additionally, businesses use these devices for digital signage and corporate communication, leveraging streaming technology for more engaging and dynamic displays.

Sample pages of Report: https://www.infiniumglobalresearch.com/form/1135?name=Sample

Regional Analysis:

North America: North America, particularly the United States, is the largest market for streaming media devices, driven by high internet penetration, a tech-savvy population, and the widespread adoption of streaming services. The region is also home to major players like Roku, Amazon, and Apple, which dominate the market.

Europe: Europe is another significant market, with countries like the UK, Germany, and France leading the adoption of streaming devices. The region's strong broadband infrastructure and growing preference for on-demand content are key factors driving market growth.

Asia-Pacific: The Asia-Pacific region is expected to experience the fastest growth during the forecast period, driven by increasing internet penetration, rising disposable incomes, and the growing popularity of OTT platforms in countries like China, India, and Japan.

Latin America and Middle East & Africa: These regions are also witnessing growth in the streaming media device market, fueled by improving internet infrastructure, the expansion of OTT services, and increasing consumer awareness of streaming technology.

Emerging Trends in the Streaming Media Device Market

Several key trends are shaping the future of the streaming media device market. The integration of voice assistants, such as Amazon Alexa and Google Assistant, into streaming devices is enhancing user convenience and personalization. The rise of 4K and 8K content is driving demand for devices that support higher resolution streaming, while advancements in High Dynamic Range (HDR) and Dolby Atmos sound are improving the overall viewing experience. Additionally, the growing focus on content aggregation platforms that offer personalized recommendations across multiple streaming services is helping consumers navigate the increasingly fragmented streaming landscape.

Major Market Players

Roku, Inc.: A leader in the streaming device market, Roku offers a range of products, from budget-friendly streaming sticks to high-end set-top boxes. Roku’s platform also supports ad-supported streaming, making it a versatile choice for consumers.

Amazon.com, Inc.: Amazon’s Fire TV devices are known for their seamless integration with Alexa, providing users with voice-controlled streaming and smart home management. Amazon’s extensive content library and ecosystem are key advantages in the market.

Apple Inc.: Apple TV is a premium streaming device offering a high-quality user experience, with features like 4K HDR support, Dolby Atmos sound, and integration with the Apple ecosystem, including Apple Arcade and Apple TV+.

Google LLC: Google’s Chromecast devices are popular for their simplicity and affordability. The latest Chromecast with Google TV offers a full-fledged streaming experience with a dedicated remote and user interface, making it competitive with other major brands.

Nvidia Corporation: Nvidia Shield TV is known for its powerful performance, making it a top choice for users who want to combine gaming and streaming. It also supports AI upscaling, enhancing the quality of lower-resolution content.

Report Overview : https://www.infiniumglobalresearch.com/market-reports/global-streaming-media-device-market

[datarep]

NVIDIA Income Statement Q3 2023

by u/giteam

[allthenewzworld]

Nvidia reported earnings after the bell that beat Wall Street expectations for earnings and guidance, and provided stronger-than-expected guidance for the current quarter.

Nvidia said it expected about $32.5 billion in current quarter revenue, versus $31.7 billion expected by analysts, according to StreetAccount. Net income during the quarter was $16.6 billion, or $0.67 per share, versus $6.18 billion, or $2.48 per share, in the year-ago period.

The company is the primary beneficiary of the ongoing artificial intelligence boom. Its market value has expanded more than nine times since the end of 2022 and was up 34% since the company's last earnings report.

Nvidia also said it approved $50 billion in share buybacks.

#allthenews

[xnewsinfo]

Nvidia and Jeff Bezos-backed Perplexity AI mentioned Thursday it plans to introduce promoting on its AI-powered search platform by the fourth quarter.Final month, the AI ​​startup launched a writer program with an preliminary group of companions together with TIME, Der Spiegel and Fortune, by which it plans to share income from interactions by which a writer’s content material is referenced.Since ChatGPT was first launched in November 2022, main search engines like google have been making an attempt to combine AI into net search, and analysts have seen AI-assisted search as a risk to Google’s dominant place within the business because the AI ​​growth started.Microsoft adopted OpenAI expertise for its Bing search engine via its seed funding, whereas Google launched AI-powered abstracts to most of the people at its developer convention in Could.In April, Perplexity AI raised $62.7 million from present buyers, together with Nvidia, and new buyers together with Garry Tan, CEO of Y Combinator, and Brad Gerstner, founder and CEO of Altimeter Capital.The fundraising spherical valued the corporate at greater than $1 billion, doubling its valuation from three months earlier.Yet one more factor! We at the moment are on WhatsApp channels! Comply with us there so that you just by no means miss any updates from the world of expertise. To observe HT Tech channel on WhatsApp, click on on right here Be a part of now!

[poonamcmi]

Artificial Intelligence In Automotive Market is Estimated to Witness High Growth Owing to Increasing Demand

Artificial intelligence (AI) in the automotive industry refers to the integration of artificial intelligence technologies in vehicles. Artificial intelligence is helping automotive manufacturers develop advanced driver-assistance systems, autonomous vehicles, predictive maintenance, and more. AI enables functionalities like autonomous emergency braking, adaptive cruise control, lane centering, advanced navigation, and cloud connectivity among others. The growing demand for enhanced driving experience, safety, and reduced road accidents is fueling the adoption of AI in automobiles.

The Global Artificial Intelligence In Automotive Market is estimated to be valued at US$ 10.72 Bn in 2024 and is expected to exhibit a CAGR of 12% over the forecast period 2024 to 2031. Key Takeaways Key players operating in the Artificial Intelligence In Automotive are BMW AG, AUDI AG, Intel Corporation, Tesla Inc, Uber Technologies, Volvo Car Corporation, Honda Motors, Ford Motor Company, NVIDIA Corporation, Tencent, Microsoft. Major players are actively investing in research and development of advanced driver assistance technologies and focusing on strategic partnerships to gain edge in the market.

The Artificial Intelligence in Automotive Market Demand predictive maintenance, in-cabin experience enhancement, smart navigation and mobility services. With advancement in machine learning and processing power, autonomous vehicles are expected to become a commercial reality in the coming years.

Globally, Asia Pacific region is expected to witness highest growth in artificial intelligence in automotive market owing to growing automotive production in countries like China and India. Growing demand for premium vehicles along with implementation of strict safety regulations will drive the adoption of AI solutions in the region. North America and Europe will also present lucrative opportunities for players operating in artificial intelligence in automotive market.

Market Drivers The key driver for growth of Artificial Intelligence In Automotive Market Size And Trends is increasing demand for advanced driver assistance systems. ADAS features like lane departure warning, adaptive cruise control and autonomous emergency braking have become standard in premium vehicles which is driving more adoption of AI. Growing investments by automotive OEMs to develop self driving vehicles is another major factor accelerating the artificial intelligence integration in automobiles. Strict safety norms by countries is also propelling the demand for AI based driver monitoring systems and accident prevention technologies in vehicles.

PEST Analysis

Political: Regulations regarding the use of AI in vehicles are still evolving, different countries have different regulations regarding the autonomous features in vehicles. Economic: With economic growth, disposable incomes are rising which is increasing the demand for advanced vehicles features. Addition of AI and autonomous features adds to the cost of vehicles but consumers are willing to pay extra for safety and convenience. ​ Social: Younger generation is more open to embrace new technological changes. Features like self-driving are attractive for the elderly and disabled population who may have difficulties driving. However, some sections also have concerns around safety, privacy and job losses resulting from AI. Technological: Advanced AI and machine learning algorithms are enabling vehicles to sense the environment, navigate and drive autonomously. Continuous advancements in technologies like sensor fusion, deep learning, computer vision etc. are enhancing the capabilities of self-driving. Cloud connectivity in vehicles is also supporting Over-The-Air updates.

In terms of value, the artificial intelligence in automotive market is concentrated majorly in North America and Europe. The US and Germany have strong presence of automotive companies investing in developing self-driving vehicles. Fast adoption of advanced technologies also contributes to their leading positions. China is also emerging as one of the fastest growing regional markets, supported by government initiatives and domestic industry players focusing on futuristic vehicles.

The Asia Pacific region excl. China is projected to be the fastest growing regional market during the forecast period. Countries like India, Japan, South Korea are witnessing higher sales of vehicles annually. Rising disposable incomes, increasing investments in building necessary infrastructure as well as evolving regulations will fuel the demand for AI-based advanced driving assistance systems and autonomous vehicles in these developing nations. Get More Insights On, Artificial Intelligence In Automotive Market About Author: Money Singh is a seasoned content writer with over four years of experience in the market research sector. Her expertise spans various industries, including food and beverages, biotechnology, chemical and materials, defense and aerospace, consumer goods, etc. (https://www.linkedin.com/in/money-singh-590844163)