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Citi stays positive on A.I. theme and lays out the key to finding … – CNBC

The early innings of the artificial intelligence trade may be over, but Citigroup is staying positive on the tech subsector, viewing cash flows as the key to unlocking the winners of the next phase. "In sum, our message is not to be overly deterred by the significant year-to-date move in profitable AI stocks," the bank said in a Friday note to clients. "Medium- to long-term opportunities still exist as the AI theme has an accelerating growth trajectory and attractive [free cash flow] dynamics that should further improve from here." So far this year, anything connected to AI has seen a significant uptick in valuation, with Nvidia shares leading the pack, surging more than 200%. While the jaw-dropping price action may suggest AI is no longer an early trade, Citi reiterated that the "initial positive thesis" looks intact and warned investors to avoid overlooking free cash flows. Citi expects many names to meet accelerated growth expectations and views free cash flows as "increasingly compelling." "Profitable stocks within this theme are already impressive cash generating machines," the bank wrote. "Recent AI developments should accentuate this characteristic and push FCF margins and growth to new highs." Given this setup, Citi screened for AI-related stocks expected to outpace market growth expectations and experience an uptick in free cash flow margins. Here are some of the stocks that made the cut: Amazon has the highest consensus expectation of more than 48% growth over the long term. Shares have gained almost 54% this year as Wall Street rotates back into technology stocks following the slump in 2022. Some investors have viewed the e-commerce giant as lagging behind its peers in the AI race. During an i nterview with CNBC this month, CEO Andy Jassy soothed some of those concerns, reiterating Amazon's plan to invest in AI across segments. Earlier this year , Amazon also unveiled a generative AI service called Bedrock for its Amazon Web Services unit, allowing clients to use language models to create their own chatbots and image-generation services. Competing chatbot heavyweight Alphabet also made the cut. Shares of the Google parent and Bard creator have rallied 38% as it battles it out with Microsoft -backed OpenAI's ChatGPT. Consensus estimates peg long-term growth at more than 17%, with a near-term free cash flow margin of nearly 24%. GOOGL YTD mountain Alphabet shares in 2023 A handful of financial stocks were also included in Citi's screen. Mastercard offers the greatest near-term free cash flow yield of the group, at 48.4%. Its long-term consensus growth estimate hovers around 19%. Shares have gained about 15% year to date. Ford Motor , Match Group and ServiceNow also made the list. CNBC's Michael Bloom contributed reporting.

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Antony Blinken & Gina Raimondo: To shape the future of AI, we must … – Financial Times

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From Hollywood to Sheffield, these are the AI stories to read this month – World Economic Forum

AI regulation is progressing across the world as policymakers try to protect against the risks it poses without curtailing AI's potential.

In July, Chinese regulators introduced rules to oversee generative AI services. Their focus stems from a concern over the potential for generative AI to create content that conflicts with Beijings viewpoints.

The success of ChatGPT and similarly sophisticated AI bots have sparked announcements from Chinese technology firms to join the fray. These include Alibaba, which has launched an AI image generator to trial among its business customers.

The new regulation requires generative AI services in China to have a licence, conduct security assessments, and adhere to socialist values. If "illegal" content is generated, the relevant service provider must stop this, improve its algorithms, and report the offending material to the authorities.

The new rules relate only to generative AI services for the public, not to systems developed for research purposes or niche applications, striking a balance between keeping close tabs on AI while also making China a leader in this field.

The use of AI in film and TV is one of the issues behind the ongoing strike by Hollywood actors and writers that has led to production stoppages worldwide. As their unions renegotiate contracts, workers in the entertainment sector have come out to protest against their work being used to train AI systems that could ultimately replace them.

The AI proposal put forward by the Alliance of Motion Picture and Television Producers reportedly stated that background performers would receive one day's pay for getting their image scanned digitally. This scan would then be available for use by the studios from then on.

China is not alone in creating a framework for AI. A new law in the US regulates the influence of AI on recruitment as more of the hiring process is handed over to algorithms.

From browsing CVs and scoring interviews to scraping social media for personality profiles, recruiters are increasingly using the capabilities of AI to speed up and improve hiring. To protect workers against a potential AI bias, New York City's local government is mandating greater transparency about the use of AI and annual audits for potential bias in recruitment and promotion decisions.

A group of AI experts, including Meta, Google, and Samsung, has created a new framework for developing AI products safely. It consists of a checklist with 84 questions for developers to consider before starting an AI project. The World Ethical Data Foundation is also asking the public to submit their own questions ahead of its next conference. Since its launch, the framework has gained support from hundreds of signatories in the AI community.

In response to the uncertainties surrounding generative AI and the need for robust AI governance frameworks to ensure responsible and beneficial outcomes for all, the Forums Centre for the Fourth Industrial Revolution (C4IR) has launched the AI Governance Alliance.

The Alliance will unite industry leaders, governments, academic institutions, and civil society organizations to champion responsible global design and release of transparent and inclusive AI systems.

Meanwhile, generative AI is gaining a growing user base, sparked by the launch of ChatGPT last November. A survey by Deloitte found that more than a quarter of UK adults have used generative AI tools like chatbots. This is even higher than the adoption rate of voice-assisted speakers like Amazon's Alexa. Around one in 10 people also use AI at work.

Nearly a third of college students have admitted to using ChatGPT for written assignments such as college essays and high-school art projects. Companies providing AI-detecting tools have been run off their feet as teachers seek help identifying AI-driven cheating. With only one full academic semester since the launch of ChatGPT, AI detection companies are predicting even greater disruption and challenges as schools need to take comprehensive action.

30% of college students use ChatGPT for assignments, to varying degrees.

Image: Intelligent.com

Another area where AI could ring in fundamental changes is journalism. The New York Times, the Washington Post, and News Corp are among publishers talking to Google about using artificial intelligence tools to assist journalists in writing news articles. The tools could help with options for headlines and writing styles but are not intended to replace journalists. News about the talks comes after the Associated Press announced a partnership with OpenAI for the same purpose. However, some news outlets have been hesitant to adopt AI due to concerns about incorrect information and differentiating between human and AI-generated content.

Developers of robots and autonomous machines could learn lessons from honeybees when it comes to making fast and accurate decisions, according to scientists at the University of Sheffield. Bees trained to recognize different coloured flowers took only 0.6 seconds on average to decide to land on a flower they were confident would have food and vice versa. They also made more accurate decisions than humans, despite their small brains. The scientists have now built these findings into a computer model.

Generative AI is set to impact a vast range of areas. For the global economy, it could add trillions of dollars in value, according to a new report by McKinsey & Company. It also found that the use of generative AI could lead to labour productivity growth of 0.1-0.6% annually through 2040.

At the same time, generative AI could lead to an increase in cyberattacks on small and medium-sized businesses, which are particularly exposed to this risk. AI makes new, highly sophisticated tools available to cybercriminals. However, it can be used to create better security tools to detect attacks and deploy automatic responses, according to Microsoft.

Because AI systems are designed and trained by humans, they can generate biased results due to the design choices made by developers. AI may therefore be prone to perpetuating inequalities, and this can be overcome by training AI systems to recognize and overcome their own bias.

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From Hollywood to Sheffield, these are the AI stories to read this month - World Economic Forum

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AI predicts the work rate of enzymes – Science Daily

Enzymes play a key role in cellular metabolic processes. To enable the quantitative assessment of these processes, researchers need to know the so-called "turnover number" (for short: kcat) of the enzymes. In the scientific journal Nature Communications, a team of bioinformaticians from Heinrich Heine University Dsseldorf (HHU) now describes a tool for predicting this parameter for various enzymes using AI methods.

Enzymes are important biocatalysts in all living cells. They are normally large proteins, which bind smaller molecules -- so-called substrates -- and then convert them into other molecules, the "products." Without enzymes, the reaction that converts the substrates into the products could not take place, or could only do so at a very low rate. Most organisms possess thousands of different enzymes. Enzymes have many applications in a wide range of biotechnological processes and in everyday life -- from the proving of bread dough to detergents.

The maximum speed at which a specific enzyme can convert its substrates into products is determined by the so-called turnover number kcat. It is an important parameter for quantitative research on enzyme activities and plays a key role in understanding cellular metabolism.

However, it is time-consuming and expensive to determine kcat turnover numbers in experiments, which is why they are not known for the vast majority of reactions. The Computational Cell Biology research group at HHU headed by Professor Dr Martin Lercher has now developed a new tool called TurNuP to predict the kcat turnover numbers of enzymes using AI methods.

To train a kcat prediction model, information about the enzymes and catalysed reactions was converted into numerical vectors using deep learning models. These numerical vectors served as the input for a machine learning model -- a so-called gradient boosting model -- which predicts the kcat turnover numbers.

Lead author Alexander Kroll: "TurNuP outperforms previous models and can even be used successfully for enzymes that have only a low similarity to those in the training dataset." Previous models have not been able to make any meaningful predictions unless at least 40% of the enzyme sequence is identical to at least one enzyme in the training set. By contrast, TurNuP can already make meaningful predictions for enzymes with a maximum sequence identity of 0 -- 40%.

Professor Lercher adds: "In our study, we show that the predictions made by TurNuP can be used to predict the concentrations of enzymes in living cells much more accurately than has been the case to date."

In order to make the prediction model easily accessible to as many users as possible, the HHU team has developed a user-friendly web server, which other researchers can use to predict the kcat turnover numbers of enzymes.

Link to the web server: https://turnup.cs.hhu.de/

Background: Machine learning and deep learning

Deep learning models comprise multi-layered artificial neural networks which can recognise and process patterns in the input data. Using large training datasets is the optimum way to train a deep learning model to process numerical inputs.

Gradient boosting models are a machine learning method, which produces large numbers of decision trees. The results of all decision trees for a specific input are used to make predictions. Similar to deep learning, training data are used to refine the model, i.e. to produce the decision trees.

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These Educators Launched One of the First AI-Themed High … – Education Week

As schools around the country grapple with how to help students and teachers grasp the implications of rapidly developing artificial intelligence technology, Seckinger High School is developing a roadmap.

It is one of the schools in the country that has made teaching AI part of its missionnot just in a one-off class or twobut infused in every subject, from language arts to social studies to English classes for non-native speakers.

Seckinger, a public high school in Gwinnett County, Ga., just outside Atlanta, opened its doors to students for the first time last fall. Principal Memorie Reesman and three teachers sat down with Education Week as part of an online forum on AI to talk about the schools AI focus.

Heres a brief transcript, edited for clarity and brevity. You can also click above to see a video of the full conversation.

Scott Gaffney, social studies teacher: The freshman class I just got done teaching this past year is going to enter an economy in 2030 likely after their undergraduate degrees are completed, and 55 percent of the workforce by then is going to be completely different than the way it looks right now. Jobs are going to be converged, diverged, reclassified.

Theres going to be new skills and capabilities across the board. Were in the midst of a new industrial revolution Our young people need to understand how AI works, whether its data science, ethics, applied experience, mathematical thinking, and creative problem-solving programming. All of these things are very useful.

Jason Hurd, computer science teacher: We have a three-year artificial intelligence pathway. The state standards were approved about two years ago. To start that off, we brought in lots and lots of stakeholders from business, big universities down to small universities here in the state of Georgia, and formed this amazing team.

In my class, in the actual artificial intelligence pathway class, which is actually a computer science class, theyre going to be diving deep. Were doing ethics, the history and evolution of AI, the programming involved in creating machine learning models.

We also offer things that are very much AI based in environmental engineering, mechanical engineering classes, regular computer science classes, ... but we have a certain spin on it at Seckinger in order to have that AI flavor.

Hurd: Thats kind of an exciting part for me as an educator. Im not going to get bored Im learning and sharing these new things with students and helping us all to evolve.

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These Educators Launched One of the First AI-Themed High ... - Education Week

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AI puts glitch in graduates’ employment plans – Higher Ed Dive

Dive Brief:

As AI becomes more integrated into the workplace, legislators are scrambling to catch up. All told, more than 160 bills and regulations related to AI were in the works as of mid-June, a management-side lawyer said in June, warning of a huge tsunami coming of state regulation.

The U.S. Equal Employment Opportunity Commission in May issued guidance on how to audit AI for discrimination to remain in compliance with Title VII of the Civil Rights Act of 1964. And the EEOC, Consumer Financial Protection Bureau, U.S. Department of Justice and Federal Trade Commission in April outlined to businesses how existing laws can apply to emerging technologies like AI.

Meanwhile, New York City started enforcing a new law requiring employers to perform bias audits on automated employment decision tools and to notify candidates of the use of those tools in their hiring process.

Amid the changing AI landscape, employers are trying to figure out how the new technology affects their hiring needs. Human cognitive skills like problem solving, creativity, originality, imagination and the ability to learn will remain in demand, even as automated tools transform the workplace, according to a July 13 report from TalentLMS. Similarly, in the Cengage Group report, 59% of employers said AI has led them to prioritize different skills in the hiring process, including uniquely human skills.

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AI puts glitch in graduates' employment plans - Higher Ed Dive

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5 Free AI Tools to Help Take Your Content to the Next Level – Entrepreneur

Opinions expressed by Entrepreneur contributors are their own.

As a multi-decade entrepreneur across various sectors including marketing, finance and technology I've spent most of my career bootstrapping companies without the assistance of artificial intelligence technologies. While I certainly leaned on my invaluable friends, professional network and mentors, I can't say I ever had ChatGPT or an AI program to help me out.

But I wish I had! Today's entrepreneurs don't know how easy they have it by comparison. Nowadays, I leverage a multitude of cutting-edge AI technologies many of which are totally free to use to help me develop my companies and provide excellent customer satisfaction.

A recent IBM survey found that 35% of businesses are using AI, and an even larger share are exploring the possibility of using AI technologies. If you want to stay competitive in tomorrow's entrepreneurial landscape, it's about time you get on board with AI, too.

In this article, I'll share my favorite AI technologies (that aren't ChatGPT) to help you take your entrepreneurial projects to the next level.

Related: 8 Reasons Using AI Will Improve Your Content Creation Process

My personal favorite AI technology of the day is Gen-2 by a lab called Runway Research. This isn't a single technology, but rather a massive suite of AI-powered tools that can totally transform your creative output. Here is just a brief glimpse at what Gen-2 is capable of doing for your business, instantly and at the click of a button:

Text-to-image generation

Text-to-video generation

Instant photo colorization

Instant audio transcription into English

Text-prompted image correction

The best use cases for Gen-2 are as follows:

Creating lifelike or cartoon-style videos for marketing campaigns

Creating social media-friendly images for social marketing posts

Generating human-like text for written marketing projects

Transcribing audio recordings of meetings or interviews into written text to save time

Personally, I use Gen-2 almost every day. As a marketer or creative worker, it's virtually indispensable.

If you want mind-blowing images to use in your marketing materials, social profiles or banner ads, I highly recommend the magic of Stable Diffusion. In my opinion, this tech is probably the best text-to-image AI service on the internet, but it comes with a far steeper learning curve especially if you use its add-on, ControlNet, which expands its possibilities.

I use Stable Diffusion for super lifelike images, which, in my opinion, is always a better option than relying on stock images. From an SEO perspective, stock images (especially common ones that have been used in thousands of other pieces of content) can have harmful effects on your search engine rankings. That's why I prefer to use totally original image content generated with Stable Diffusion rather than stock image services.

This one is a lightweight Chrome extension that anyone can use without any prompt engineering skills. Quilbot is a terrific paraphrasing tool that can take any text and rewrite it near-flawlessly in a matter of seconds.

Now, it's important that you don't use this tool to plagiarize or steal someone else's ideas. Rather, this tool is best used for two legitimate purposes:

As a Grammarly replacement that spellchecks and fixes tone and grammar

As an SEO tool to refresh or rephrase old content

Google's PageRank algorithm favors content that is frequently updated. I use Quilbot to rewrite portions of old blog posts or pages, and fairly often, the result is that the content sees an SEO ranking boost within a week or two of the new content going live.

Related: The Complete Guide to Effectively Using AI Writing Tools in Content Marketing

Surfer SEO has been around for years long before ChatGPT kicked off the consumer AI revolution last year. However, it's only now getting the praise it rightly deserves. Basically, Surfer SEO is an optimization tool to ensure that your on-page elements (i.e., text, metadata, titles, formatting and images) are perfectly utilized to improve your search engine performance.

This tool is quite affordable, and many savvy SEO specialists have used it since 2019. I can personally attest that this tool is the real deal, and I run every blog post I publish through Surfer SEO's Content Editor before it's released. Be warned, however, that Surfer SEO does tend to "over-optimize" in some cases, so don't feel tempted to apply all of the tool's recommendations to each and every blog post you write.

Any written or social content provides way more value if there are charts, tables and graphs that help visualize numerical data. The problem is that it's a pain to create original graphs and charts, especially if you're not exactly a math whiz.

Fortunately, GraphMaker makes it way easier for me to quickly whip up visually captivating graphs that add a ton of value for my readers. For example, if you plug in inflation rates over time alongside, say, the U.S. exchange rate against the British Pound Sterling, you'll get a wonderful line chart that depicts how inflation impacts the strength of the U.S. dollar.

It's one thing to tell your readers about the subject at hand but it's far superior to show them. I recommend using this tool to help show and demonstrate numerical phenomena to your readers, which is always a great idea for captivating their attention.

Related: Top 5 Ways AI Can Enhance Your Content-Creation Process

If you think a simple OpenAI account and a knack for prompting ChatGPT will cut it in tomorrow's market, think again. Your competitors are using a diverse variety of AI technologies, and I suggest you adapt to these changing circumstances if you want to stay afloat as well.

My advice is to use the technologies I've listed above as a mere starting point in your journey. New AI tools are being released every day, so I recommend staying abreast of the industry and experimenting with new AI software as they come out. The early adopters of these technologies will, more often than not, find themselves at a competitive advantage in their industry.

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AI: How far is China behind the West? – The Indian Express

Chinese tech giants are speeding to catch up with their US peers in the creation of artificial intelligence (AI) chatbots. The worlds second-largest economy is on course to spend $15 billion (13.5 billion) on AI projects this year alone, a rise of nearly 50% in just two years.

Even before the arrival of large language models like the Microsoft-backed Chat GPT, some tech experts refused to bet that the West would dominate the AI race, despite the most advanced AI labs being located in the US and UK.

Kai-Fu Lee, the Taiwanese computer scientist, venture capitalist and tech executive predicted in 2018 that China would quickly surpass the US as an AI superpower, insisting the technology had already passed the innovation stage.

Lee argued that the world was now in the AI implementation stage, where China has the edge, due to years of state surveillance. Snooping on the Chinese population has allowed the accrual of huge amounts of data, which AI platforms harness to improve their learning.

Strong growth ahead

But while more than half of the estimated 1 billion surveillance cameras on the planet have been deployed in China, Lees critics argue that the AI revolution is still in its infancy and the West still holds the key.

The big innovations in AI havent happened yet far from it [] and the US currently has the advantage in that area, Pedro Domingos, professor emeritus at the Paul G. Allen School of Computer Science & Engineering at the University of Washington, told DW.

Domingos spoke of large data having diminishing returns, in that China wont get a lot more benefit from snooping on its 1.4 billion population than the US does, with its 332 million inhabitants.

The diversity of the data also matters. I would prefer to have the data from, say, Europe than China as it is more diverse and therefore you can learn more from it.

The US is clearly troubled by Beijings technological ambitions, especially as the official Chinese government policy is to make the country the worlds dominant AI player by 2030.

Chip curbs delays Beijings ambitions

Ever-worsening relations between Washington and Beijing led the US last year to put export curbs on the most advanced memory chips, which Chinese firms need for their own advanced AI language models.

The most cutting-edge AI systems require massive amounts of hardware thousands of very specialized chips, running for weeks or months at a time, Paul Scharre, executive vice president and director of studies at the Center for a New American Security, told DW.

Denying China access will shut them out of building the most advanced systems and that gap is likely to widen over time as chip technology continues to advance.

Chinese tech firms may find other ways around the ban. The domestic semiconductor market is likely to see an investment boom as local producers race to improve their own chips.

Is the West giving it away?

Another hole Washington may seek to close is how the US machine learning platforms are currently open source freely available to be copied and modified.

If you have access to the trained AI model you dont need the advanced chips. So there is a real risk that the export controls will become ineffective, Scharre, the author of the book Four Battlegrounds: Power in the Age of Artificial Intelligence, warned.

Indeed, Chinas own versions of Chat GPT, created by the likes of e-commerce giant Alibaba and social media platform Baidu, were released to the world in April, just months after their US rivals.

Chinese tech sector tamed

But the country has lots of other hurdles to overcome before it rules the AI space. For one, President Xi Jinpings crackdown on the power of the tech sector over the past two years likely made Chinese executives more risk-averse.

Youve seen an explosion in rules and enforcement for the tech sector, Karman Lucero, a fellow at the Paul Tsai China Center, at Yale Law School, told DW. Often it [the enforcement] has been very opaque and has even preceded the new rules, which has a chilling effect on the industry.

Lucero noted how the Chinese governments obsession with censorship could be their Achilles heel as AI models wont realize their full learning potential with large amounts of missing data or when programmed to avoid many off-limit topics.

In China, you have this wide range of [censorable] content that is always shifting. Something that could be a permissible topic today could be prohibited tomorrow, and theres no way to predict it.

Brain drain inevitable

The country is also short of skilled workers needed to achieve Beijings goals. Despite an effort to build an army of AI talent, retaining top tech workers is a challenge when their skills are in demand globally.

Talent exodus is a major hindrance to Chinas authoritarianism in that it drives people away. Chinas top AI scientists leave and its not just that they go abroad to study and work, they prefer a more democratic way of life, Scharre said.

Despite these issues, he thinks Chinas AI labs are just 18 months behind the current leading research labs in the West and that the country already has the edge when it comes to deploying AI across society.

China undeterred

While some in the West still question whether the rollout of AI should be paused over safety concerns, Domingos says China is going full steam ahead in exploiting what he said was a dream tool for an autocrat.

For us in the democratic world, its absolutely essential that the US comes out ahead. If China does, were in a lot of trouble politically, economically and militarily, he warned.

In the same way that US culture and technology spread globally over the past century, Domingos argued that Chinas domination of AI would make the rest of the world more like them, giving the example of how the West quickly followed China into strict lockdowns when COVID first hit.

In some ways, it may be harmless there are many great things about China but as far as their ideology goes, it is very dangerous.

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AI: How far is China behind the West? - The Indian Express

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New AI technology helps detect wildfires in Calfiornia – CBS News 8

SAN DIEGO The future of fighting wildfiresis here. Artificial intelligence is helping firefighters detect smoke and the technology is being used in California.

Responding to a fire quickly can mean the difference between a small brush fire or a catastrophic wildfire. Now AI is being used to help spot fires before humans can.

The company Pano AI has deployed their technology in six states including California.

"We mount ultra high definition security cameras on mountaintop locations on cell towers. We rotate the cameras 360 degrees every minute to look for the first wisps of smoke," said Sonia Kastner, the founder of Pano AI.

Kastner says their algorithm helps AI identify smoke early on and decipher it between clouds or dust. The detection is verified by a human before it's passed along to first responders.

"Makes it easier for emergency managers to coordinate with each other. Make smart decisions and get to the fire faster to nip it in the bud before it becomes a mega fire," she said.

She says only one in 20 emergency calls for wildfires are true wildfires but all 20 of those calls must be investigated. The AI technology helps cut down on false alarms and prevents wasting resources. Right now CAL Fire is using AI. They have cameras in Riverside and San Bernardino County that can detect abnormalities like smoke.

"We're able to get instant situational awareness with what's going on with these fires. if they point the camera in and the fire looks like it's a large black column in the middle of no where then we're going to send a lot of resources immediately," said Michael Cornette, a fire captain for CAL Fire.

Pano AI says it's continuing to expand and is rolling out in Rancho Palos Verdes. As for San Diego, its not up and running right now, however CAL Fire is working alongside SDSU on the technology.

WATCH RELATED: Marine Corps Air Station Miramar firefighters fight flames for San Diego community (July 2023).

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New AI technology helps detect wildfires in Calfiornia - CBS News 8

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If I Could Buy Only 1 AI Stock Right Now, This Would Be It – The Motley Fool

Artificial intelligence (AI) is for real. The amazing progress in AI -- and the skyrocketing share prices of AI leaders -- has proven it over the last several months.

My portfolio is worth considerably more now than at the end of 2022 because of the AI boom. I like several AI stocks. But if I could buy only one AI stock right now, which would it be?

I only have to glance at the stocks that have been big winners for me to find several top AI contenders. Microsoft made a brilliant move by investing heavily in OpenAI and partnering with the company to integrate ChatGPT into its own products. My only regret with Microsoft is that I wish I had owned more shares.

Nvidiahas absolutely crushed it this year. We might have to change the old saying that something is "selling like hotcakes" to "selling like GPUs," the graphics processing units Nvidia markets that are ideal for powering AI systems.

Meta Platformsis another great performer so far in 2023. The company is best known for its social media platform, which now includes the wildly popular Threads app. But Meta's open-source approach has made it a serious contender in AI as well.

Amazon has made its mark in AI, too. It has introduced multiple new AI products that should make its Amazon Web Services cloud platform even more attractive to developers.

There are also quite a few promising AI stocks that I haven't bought. However, the one AI stock I'd buy right now is already a major holding for me -- Google parent Alphabet (GOOG 1.30%) (GOOGL 1.26%).

Alphabet clears several hurdles in a way that the other contenders don't.Valuation stands at the top of the list.

My colleague Travis Hoium thinks that Alphabet stock is "insanely cheap." I wouldn't go quite that far, but I certainly agree with the overall sentiment, especially in comparison with most of the other AI leaders.

Alphabet shares trade at a forward price-to-earnings ratio of less than 23. That's a bargain price when you stack it up against Nvidia's forward earnings multiple of 62. If a big pullback is on the way (and I suspect one is), Alphabet stock should fare better than many of its high-flying brethren.

I also think Alphabet has firmly established its AI credentials. Some thought it could be in trouble after the early success of ChatGPT and the less-than-stellar debut of the company's own Google Bard. However, Alphabet has held its own. I have personally seen the company dramatically improve Bard over time as well as introduce other impressive AI innovations.

Alphabet's financial position is another huge plus, in my view. It's highly profitable. The company has a cash stockpile of more than $115 billion.

Finally, Alphabet is arguably the top leader in one area that could turbocharge AI advances and adoption -- quantum computing. There's still a long way to go before quantum computing technology might achieve its potential. Maybe it never will. But if any company can make it happen, it's Alphabet.

Some argue that Alphabet is a risky proposition because of AI. They maintain that Google Search could be disrupted by chatbots or other AI apps. I understand those concerns, but I believe that Alphabet is less risky than they think.

For one thing, Google Search's market share has held relatively steady, according to Bank of America analysts Justin Post and Joanna Zhao. A BofA survey even found that 45% of ChatGPT users will use Google Search even more with the integration of generative AI.

Anecdotally, I've found that I use Google Search as much as I ever have with subjects that tend to attract advertisers. And I use ChatGPT, Bard, and other chatbots quite a bit. I also have access to Google Search's experimental conversational AI integration and find it helpful.

My view is that the biggest risk for any AI stock over the near term is related to valuation. As previously mentioned, Alphabet competes especially well on this front.

I predict that multiple stocks will be huge winners over the next decade and beyond with the increased adoption of AI. But at least for right now, in my opinion, Alphabet is the most attractive of the bunch.

Suzanne Frey, an executive at Alphabet, is a member of The Motley Fool's board of directors. John Mackey, former CEO of Whole Foods Market, an Amazon subsidiary, is a member of The Motley Fool's board of directors. Randi Zuckerberg, a former director of market development and spokeswoman for Facebook and sister to Meta Platforms CEO Mark Zuckerberg, is a member of The Motley Fool's board of directors. Bank of America is an advertising partner of The Ascent, a Motley Fool company. Keith Speights has positions in Alphabet, Amazon.com, Bank of America, Meta Platforms, and Microsoft. The Motley Fool has positions in and recommends Alphabet, Amazon.com, Bank of America, Meta Platforms, Microsoft, and Nvidia. The Motley Fool has a disclosure policy.

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If I Could Buy Only 1 AI Stock Right Now, This Would Be It - The Motley Fool

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