Mediaboss Marketing

SAN FRANCISCO A growing group of Wall Street analysts and tech investors is beginning to sound the alarm that the immense amount of money being poured into artificial intelligence by Big Tech companies, stock market investors and venture-capital firms could be leading to a financial bubble.

On Tuesday, analysts on Googles quarterly conference call peppered chief executive Sundar Pichai with questions about when the companys $12-billion-a-quarter investment in AI would begin paying off. And in the past few weeks, big Wall Street investment banks including Goldman Sachs and Barclays, as well as VCs such as Sequoia Capital, have issued reports raising concerns about the sustainability of the AI gold rush, arguing that the technology might not be able to make the kind of money to justify the billions being invested into it. Stock prices for big AI names including Google, Microsoft and Nvidia are all up significantly this year.

Despite its expensive price tag, the technology is nowhere near where it needs to be in order to be useful, Jim Covello, Goldman Sachss most senior stock analyst and a 30-year veteran of covering tech companies, said in a recent report about AI. Overbuilding things the world doesnt have use for, or is not ready for, typically ends badly.

Covellos comments are in sharp contrast to a different Goldman Sachs report from just over a year ago, in which some of the banks economists said AI could automate 300 million jobs around the world and increase global economic output by 7 percent in the next 10 years, spurring a spate of news coverage about the disruptive potential of AI.

Barclays said Wall Street analysts are expecting Big Tech companies to spend around $60 billion a year on developing AI models by 2026, but reap only around $20 billion a year in revenue from AI by that point. That kind of investment would be enough to power 12,000 products of a similar size to OpenAIs ChatGPT, Barclays analysts wrote in a recent report.

OpenAI released ChatGPT in November 2022, kicking off a race in Silicon Valley to build new AI products and get people to use them. Big Tech companies are spending tens of billions of dollars on the technology. Retail investors have bid up the price of those companies and their suppliers, especially Nvidia, which makes the computer chips used to train AI models. Year to date, shares of Google parent Alphabet are up 25 percent, Microsoft is up 15 percent, and Nvidia shares are up 140 percent.

Venture capitalists have also poured billions more into thousands of AI start-ups. The AI boom has helped contribute to the $55.6 billion that venture investors put into U.S. start-ups in the second quarter of 2024, the highest amount in a single quarter in two years, according to venture capital data firm PitchBook.

Tech executives insist that AI will change whole swaths of modern life, in the same way the internet or mobile phones did. AI technology has indeed improved drastically and is already being used to translate documents, write emails and help programmers code. But concern over whether the tech industry will be able to recoup the billions of dollars its investing in AI anytime soon or ever has risen among some firms that only last year were heralding the boom.

We do expect lots of new services but probably not 12,000 of them, Barclays analysts wrote. We sense that Wall Street is growing increasingly skeptical.

In April, Meta, Google and Nvidia all signaled their commitment to going all in on AI by telling investors during quarterly earnings calls that they would ramp up the amount of money theyre spending on building data centers to train and run AI algorithms. Google reiterated Tuesday it would spend more than $12 billion a quarter on its AI build-out. Microsoft and Meta are due to report their own earnings next week and may give further indication about their AI road maps.

Pichai said Tuesday that it would take time for AI products to mature and become more useful. He acknowledged the high cost of AI but said even if the AI boom slows down, the data centers and computer chips the company was buying could be put to other uses.

The risk of underinvesting is dramatically greater than the risk of overinvesting for us, Pichai said. Not investing to be at the front here has much more significant downsides.

A spokesperson for Microsoft declined to comment. A spokesperson for Meta did not respond to a request for comment.

Vinod Khosla, who co-founded computer network systems company Sun Microsystems and is one of Silicon Valleys most influential venture-capital investors, compared AI to personal computers, the internet and mobile phones in terms of how much it would affect society.

These are all fundamentally new platforms. In each of these, every new platform causes a massive explosion in applications, Khosla said. The rush into AI might cause a financial bubble where investors lose money, but that doesnt mean the underlying technology wont continue to grow and become more important, he said.

There was a dot-com bubble, according to Goldman Sachs, because prices went up and prices went down. According to me, internet traffic didnt go down at all.

As AI changes the way people work, do business and interact with one another, many start-ups will fail, he said. But overall the industry will make money on AI. He predicts there will eventually be multiple trillion-dollar businesses in AI, such as humanoid robots, AI assistants and programs that can completely replicate the work of highly paid software engineers.

But so far, AI is not contributing to an increase in venture capital getting a return on those investments. The amount of money made in venture capital exits, which represent initial public offerings or acquisitions of tech start-ups, fell to $23.6 billion in the second quarter, down slightly from $25.4 billion the previous quarter, according to PitchBook.

The tech industry would need to generate around $600 billion in revenue a year to make up for all the money being invested in AI right now, yet it is far from close to that number, David Cahn, a partner at venture firm Sequoia Capital, wrote in a blog post last month.

Speculative frenzies are part of technology, and so they are not something to be afraid of, Cahn said. But we need to make sure not to believe in the delusion that has now spread from Silicon Valley to the rest of the country, and indeed the world. That delusion says that were all going to get rich quick.

Microsofts and Googles revenue are growing, especially in their cloud businesses where they sell access to AI algorithms and the storage space to use them. Executives from the companies say AI is driving new interest in their products and will become a major moneymaker in the future. But some analysts are pointing out that there have been very few hugely successful stand-alone products, besides OpenAIs ChatGPT and Microsofts coding assistant GitHub Copilot.

Wall Street is growing increasingly skeptical given that ChatGPT and GitHub Copilot are the two breakout successes in consumer and enterprise thus far 20 months in, the Barclays analysts wrote in their report.

The cost of developing and running AI programs will come down as other companies compete with Nvidia and the technology becomes more efficient, said Vineet Jain, CEO of Egnyte, an AI and data management company. For now, the cost of providing AI products is too expensive, and he doesnt expect to make any AI-specific revenue this year. But as costs go down and demand continues to rise, that will change, Jain said.

The value proposition is absolutely there, but the expectation right now is still unrealistic, he said, referring to the frenzy to sell AI products to consumers and businesses.

Some start-ups have already come down from the heights of the early part of the AI boom. Inflection AI, a start-up founded by veterans of Googles famous DeepMind AI lab, raised $1.3 billion last year to build out their chatbot business. But in March, the companys founders left for jobs at Microsoft, taking some of their top employees with them to the tech giant. Other AI companies, like Stability AI, which was one of the first companies to build a widely popular AI image generator, have had to lay off workers. The industry is also facing lawsuits and regulatory challenges.

Bigger companies like Google and Microsoft will be able to keep spending money until demand for AI products increases, but smaller start-ups that have taken on a lot of venture capital might not survive the transition, Jain said.

Its like a souffl that keeps popping up and popping up, it has to come down a bit.

Go here to see the original:

Big Tech says AI is booming. Wall Street is starting to see a bubble. - The Washington Post

Capitol photo by Martin Jacobsen, CC license

In January, during a Democratic primary, thousands of voters received a robocall that used artificial intelligence to impersonate President Biden discouraging them from voting.

The political consultant responsible is now facing millions in fines and jail time for the 13 felony counts of voter suppression and 13 counts of impersonating a candidate, a misdemeanor.

To combat this new threat of AI deep fakes and misinformation in US elections, a new Artificial Intelligence Task Force is bringing together state and local elected officials to focus on ways to combat malicious AI-generated activity that threaten the democratic process.

Arizona Secretary of State Adrian Fontes doesnt speak German, but he created a deepfake that makes it nearly impossible to tell that it isnt actually Fontes speakingall to demonstrate just how alarmingly lifelike and manipulative AI-generated content can be.

Fontesalong with Michigan Secretary of State Jocelyn Benson and Minnesota Secretary of State Steve Simonare leading the fight to prepare election workers and voters in their states to be vigilante and savvy against the AI threats.

They are part of a coalition of secretaries of state working with the task force, created by the NewDEAL Forum, to develop tools and best practices to combat AI disinformation this election season.

In Michigan, weve enacted legislation to make it a crime for someone to knowingly distribute materially-deceptive deep fakes that are generated by AI when there is an intent behind it of harming the reputation of or the electoral prospects of a candidate, Secretary of State Benson told Democracy Docket, a digital news platform founded by attorney Marc Elias dedicated to voting rights and elections in the courts.

The new law, passed in November, makes that crime a felony.

GREAT NEWS ON CRIME: US Crime Rate Drops to Historic Lows With Murders, Rapes, and Robbery Plunging, New Statistics Show

In addition to that, we require any political advertisements that are generated in whole or substantially with the use of AI to include a statement that that ad was generated by artificial intelligence. That disclaimer requirement helps equip citizens with the knowledge of how to be critical consumers.

Both the important swing states of Arizona and Michigan have developed tabletop exercises to train election clerks to identify AI, and to practice linking them with law enforcement and first Responders, both for security and to rapidly respond to issues that may occur around voting, on or before election dayand also to be prepared to stop the negative impact of AI from spreading. (See their interviews in the video below)

A NewDEAL Forum poll conducted in Arizona in April found that only 41% of respondents knew anything about AI and elections.

Generative AI presents both tremendous opportunities and significant challenges, said New York State Assemblymember Alex Bores, Co-Chair of the NewDEAL Forum AI Task Force, and one of the few state legislators with a computer science background. Our goal is to craft policies to harness AIs potential to improve public services while proactively preparing for the threats and unforeseen challenges it poses to our democratic institutions.

In March, they published a report that outlines best practices for election officialsfrom secretaries of state to county election workersto mitigate the negative impacts of AI in elections. The advice includes more short-term practices, like public information campaigns about the threats, and protocols for a rapid response when they do arise.

VOTER RIGHTS VICTORY: 2 Conservatives on Supreme Court Seal Historic Decision to Preserve Voting Rights in Alabama Gerrymandering Case

The document also suggests legislation that state politicians can pass to help protect democracy from AI threats.

According to Democracy Docket, at least 40 states are introducing legislation to regulate the use of AI, but only 18 have laws that specifically address election-related AIand thankfully, now Michigan is one of them.

WATCH a discussion with Fontes and Benson on Democracy Docket (Subscribe to stay up to date with court cases around the US involving elections.)

PLEASE HELP TO SPREAD AWARENESS By Sharing the News on Social Media

Read the original here:

New AI Task Force Led By Michigan and Arizona Combats Deep Fakes and Election Misinformation in US - Good News Network

OpenAI is announcing its much-anticipated entry into the search market, SearchGPT, an AI-powered search engine with real-time access to information across the internet.

The search engine starts with a large textbox that asks the user What are you looking for? But rather than returning a plain list of links, SearchGPT tries to organize and make sense of them. In one example from OpenAI, the search engine summarizes its findings on music festivals and then presents short descriptions of the events followed by an attribution link.

In another example, it explains when to plant tomatoes before breaking down different varieties of the plant. After the results appear, you can ask follow-up questions or click the sidebar to open other relevant links. Theres also a feature called visual answers, but OpenAI didnt get back to The Verge before publication on exactly how this works.

SearchGPT is just a prototype for now. The service is powered by the GPT-4 family of models and will only be accessible to 10,000 test users at launch, OpenAI spokesperson Kayla Wood tells The Verge. Wood says that OpenAI is working with third-party partners and using direct content feeds to build its search results. The goal is to eventually integrate the search features directly into ChatGPT.

Its the start of what could become a meaningful threat to Google, which has rushed to bake in AI features across its search engine, fearing that users will flock to competing products that offer the tools first. It also puts OpenAI in more direct competition with the startup Perplexity, which bills itself as an AI answer engine. Perplexity has recently come under criticism for an AI summaries feature that publishers claimed was directly ripping off their work.

OpenAI seems to have taken note of the blowback and says its taking a markedly different approach. In a blog post, the company emphasized that SearchGPT was developed in collaboration with various news partners, which include organizations like the owners of The Wall Street Journal, The Associated Press, and Vox Media, the parent company of The Verge. News partners gave valuable feedback, and we continue to seek their input, Wood says.

Publishers will have a way to manage how they appear in OpenAI search features, the company writes. They can opt out of having their content used to train OpenAIs models and still be surfaced in search.

Responses have clear, in-line, named attribution and links

SearchGPT is designed to help users connect with publishers by prominently citing and linking to them in searches, according to OpenAIs blog post. Responses have clear, in-line, named attribution and links so users know where information is coming from and can quickly engage with even more results in a sidebar with source links.

Releasing its search engine as a prototype helps OpenAI in a few different ways. First, if SearchGPTs results are wildly incorrect like when Google rolled out AI Overviews and told us to put glue on our pizza its easier to say, well, its a prototype! Theres also potential for getting attributions wrong or maybe wholesale ripping off articles like Perplexity was accused of doing.

This new product has been whispered about for months now, with The Information reporting about its development in February, then Bloomberg reporting more in May. We reported at the same time that OpenAI had been aggressively trying to poach Google employees for a search team. Some X users also noticed a new website OpenAI has been working on that hinted toward the move.

OpenAI has slowly been bringing ChatGPT more in touch with the real-time web. When GPT-3.5 was released, the AI model was already months out of date. Last September, OpenAI released a way for ChatGPT to browse the internet, called Browse with Bing, but it appears a lot more rudimentary than SearchGPT.

The rapid advancements by OpenAI have won ChatGPT millions of users, but the companys costs are adding up. The Information reported this week that OpenAIs AI training and inference costs could reach $7 billion this year, with the millions of users on the free version of ChatGPT only further driving up compute costs. SearchGPT will be free during its initial launch, and since the feature appears to have no ads right now, its clear the company will have to figure out monetization soon.

Read more here:

OpenAI announces SearchGPT, its AI-powered search engine - The Verge

The excitement surrounding artificial intelligence (AI) has been a major driver of the stock market rally this year, with the market value of generative AI estimated to be around $1 trillion.

AIs potential to enhance productivity and transform industries such as marketing, healthcare, and manufacturing has fueled a surge in demand for leading tech companies. This surge has significantly boosted the stock prices of firms specializing in semiconductors and servers.

In this context, Finbold analyzed the ongoing trends and tracked down the two best investments in the AI sector for the upcoming month.

As companies increasingly digitize their operations to enhance efficiency, ServiceNows (NYSE: NOW) AI and machine learning-driven workflow solutions have positioned it as a market leader.

The companys financial performance in Q2 was impressive, with subscription revenues rising by 23% on a currency-adjusted basis to $2.54 billion.

ServiceNow secured 88 high-value deals, each worth over $1 million in annual contract value, marking a 26% year-over-year increase, demonstrating strong demand among large enterprises.

Investors are particularly excited about ServiceNows integration of generative AI (GenAI), as the company aims to revolutionize workflows across industries with GenAI at its core.

Looking ahead, ServiceNows forward guidance is equally promising. The company expects Q3 sales to range between $2.66 billion and $2.665 billion, indicating a robust 20.25% annual growth at the midpoint.

Additionally, ServiceNow anticipates an operating income margin of 29.5%, reflecting strong operational efficiency. Valuation metrics also show the companys potential, with a market cap of $169.66 billion and an enterprise value of $166.50 billion.

Despite high trailing and forward PE ratios of 149.93 and 55.85 respectively, the companys PEG ratio of 2.89 suggests reasonable valuation given its growth prospects.

Analyst sentiment further supports the bullish outlook, with an average 12-month price target of $870.04, representing a 5.13% upside from the current price of $827.61.

High institutional ownership, at 90.72%, also highlights strong professional investor confidence, giving it a strong buy rating.

Micron Technology (NASDAQ: MU) has experienced a remarkable 30% stock surge this year, driven by soaring demand for its high-performance memory modules from AI servers.

As a key supplier of DRAM and NAND memory for PCs and data centers, Microns AI-tailored high-bandwidth memory chips have sold out for 2024, prompting the company to raise prices.

These price increases have significantly improved its gross margin, which rose to 27% in Q3 from 19% in Q2, with an expected rise to 34% in Q4.

This AI-fueled demand also led to an 82% year-over-year revenue increase to $6.8 billion in Q3, with projections of $7.6 billion for Q4, marking a 90% increase from the previous year.

Analysts have responded positively, with KeyCorp, Needham & Company, JPMorgan Chase (NYSE: JPM), and Barclays all raising their price targets to as high as $180 and maintaining buy or overweight ratings.

Valuation metrics include a forward PE ratio of 19.65, a PS ratio of 5.68, and a PEG ratio of 1.12, indicating robust growth potential relative to earnings.

Analyst sentiment further supports the bullish outlook, with an average 12-month price of $169.08, a high forecast of $225, and a low forecast of $140.The average price target shows a 54.54% change from the last price of $109.41.

Institutional ownership stands at 84.58%, reflecting strong confidence from professional investors, giving it a strong buy rating.

Investors looking to capitalize on the AI boom should consider these stocks, as they offer promising returns in the evolving technological landscape.

Disclaimer: The content on this site should not be considered investment advice. Investing is speculative. When investing, your capital is at risk.

Read more:

Buy alert: 2 AI stocks with strong buy ratings for August 2024 - Finbold - Finance in Bold

Copilot+ PCs are about to enter their confusing era with the Asus Zenbook S 16, as we welcome x86 to the party bringing its own set of pros and cons that Ill go into.

To talk about whats going on here, the first of these new laptops packing Snapdragon X Elite rely on Arm processing. This is a mobile-first chip architecture that breaks down complex tasks into the barebones instructions and completes a single one with every tick of that processors clock cycle (otherwise known as Reduced Instruction Set Computing (RISC).

And with this choice, you get key benefits that are important to laptop users like striking that fine balance between maximizing power and giving you a nice, long battery life (as can be seen in the battery behemoth that is the HP Omnibook X).

Meanwhile, at Computex 2024, we learnt more about what Intel and AMD is bringing to the mix in terms of its x86 chipsets the architecture used for Windows PCs for over 30 years that uses Complex Instruction Set Computing (CISC) to tackle every part of a task equally. Its done the job well over those three decades, but has historically been the source behind a lot of Windows laptop battery life woes.

It made me nervous-excited in the build up to actually being able to test a laptop with the AMD Ryzen AI 9 HX 370 (what a name), and some of my nervousness has been proven right. While the Zenbook S16 is certainly improved in the battery life department when compared with other x86 laptops, it still falls behind Arm-based systems. Not only that, but we uncovered slower general performance and disk loading speeds too.

Which leaves me feeling really conflicted, because I do like the Zenbook S16 its OLED display is a feast for the eyes, keyboard and touchpad ergonomics are on point, it is very graphically capable, you wont run into any Arm-based app compatibility issues, and I absolutely adore the ceraluminum finish and premium aesthetic.

However, while it does indeed outperform the M3 MacBook Air, the nitty gritty of the results give off the vibe that this laptop is being slightly held back by the past. It makes you really think about whether it's time for Microsoft to fully turn into Arm processing for itself and other laptop makers. And I know that sort of incendiary statement brings a tonne of work for developers turning their apps and games to Arm or relying on the Prism emulation layer.

But as the Copilot+ PC world starts to get a little more confusing, this can all be boiled down to one question you need to ask yourself: do you want compatibility comfort at the expense of worry-free battery life, or sit through the transition of several Windows apps to Arm and embrace a more perfect balance between power and stamina with a Snapdragon system?

And the more I think about it, the more Im realizing that there may only be one correct answer here

This is our first step into AMDs Strix Point, so lets get to the (ahem) point. Yes, AMD Ryzen AI 9 HX 370 is a powerhouse in plenty of areas that puts the M3 MacBook Air on notice. Not only that, but Asus attention to the aesthetics and ergonomics makes this rather nice to use.

Asus struck gold with its design refresh involving these clean lines and utilitarian branding, and the Zenbook S 16 continues this trend with a gorgeously sophisticated notebook. It all starts with that ceraluminum finish (PR-speak for a ceramic/aluminum composite), which gives the lid an incredible textured finish that feels great to the touch and eliminates any fingerprints.

Its also impressively thin and light for a 16-inch laptop, though the MacBook Air does pip it in thinness and the Surface Laptop 7 edges below in weight.

Then you open it up, and youre greeted by a mouthwatering OLED screen (more on that later) alongside a fantastic keyboard/touchpad combination. In some ways, the touchpad reminds me of the Huawei MateBook X Pro giving you controls over the brightness, volume and video scrubbing along the edges of it along with a smooth multi-touch surface.

Meanwhile, the keyboard is nicely spaced out with plenty of comfortable travel on each individual key. Put simply, youll really enjoy getting stuff done on here.

I was recently an OLED convert, and the Zenbook S 16 continues my love affair with the panel technology a flash flood of accurate color for all your productivity and entertainment purposes. While LCD continues to pip it in terms of brightness, Id happily give up a little bit of that in favor of this vividity.

In terms of that accuracy, the MacBook Airs Liquid Retina panel does come close enough that you wont really tell the difference in the sRGB gamut. But its in things like watching super colorful shows or making the most of that deep contrast ratio where the S 16 really comes into its own.

So lets dabble with the AMD Ryzen AI 9 HX 370 in here. With 12 cores and 24 threads clocked at up to 5.1 GHz, it is capable of handily defeating the M3 MacBook Air and even comes close to taking on M3 Pro. When compared to Snapdragon X Elite, the picture is a little bit mixed, but were entering an era where Windows laptops are becoming more capable of taking on Apple silicon.

Where it does beat Snapdragon, however, is in three key areas:

Of course, these 3DMark results may be skewed slightly by the fact that they rely on x86 architecture, which means the Surface Laptop 7s Snapdragon X Elite will have to run it through Prism translation. However, this is a realistic representation given the job of rebuilding a lot of apps to make the most of Arm is well underway and will take a while to finish. So a compromise in performance is expected.

A complicated picture is being painted by the new AMD chips here. On one hand, they are indeed more powerful in certain areas. But its almost as if the Zenbook S 16 is being slightly hamstrung from really competing with the Arm likes of Snapdragon X Elite and Apple silicon.

If we were in a world where all Windows laptops were x86 and Microsofts Arm efforts were still a bit of a joke, I would be here telling you how the battery life has improved over the likes of Intel Core Ultra (which it has).

But were not. Were in a new era where Windows 11 systems are capable of outlasting MacBooks, so its time to alter expectations:

As you can see, the not-so-power-efficient nature of x86 means it falls behind its competition by at least a couple of hours.

Plus, in what seems to be a symptom of most Copilot+ PCs weve tested, while thermal management has improved over last generation chips, they do still get noticeably hotter than Apples notebooks.

As you saw from the performance charts up above, the margins between AMD and Qualcomm are fine, but there is a difference here in Geekbench scores, SSD transfer speeds and the way it handles transcoding video.

In practice, these wont be the biggest dips in performance in real world use. I experienced extremely little slowdown under intense multitasking pressure. But the numbers dont lie, and with both the Arm Surface Laptop 7 and x86 Zenbook S 16 coming in at near-identical prices, you are getting a slightly better price-to-performance ratio when it comes to tackling multi-core tasks and loading up big files.

Copilot+ PCs are entering their confusing era, as not every chip will give you the same experience youd expect from reading our current crop of reviews.

The Asus Zenbook S 16 is, in many ways, a good laptop. The OLED display is a spectacle encased in that beautiful ceraluminum shell with a top notch keyboard and touchpad. Not only that, but sticking to x86 gives you no issues with app compatibility while Windows developers scramble to create Arm versions.

However, you cant stop the feeling that maybe, just maybe, Strix Point plays second fiddle to Snapdragon X Elite. I mean there are some areas where it reigns supreme, such as integrated graphics and AI processing with that larger NPU.

But the Arm variant of Copilot+ PCs strikes a better balance between performance and power efficiency something that I would pick even though running into some apps that just dont work yet can be frustrating.

Original post:

I just tested Asus first AMD Ryzen AI Copilot+ PC can it beat Snapdragon X Elite? Sort of - Tom's Guide