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Indian AI Anchorwoman Lisa Introduces Herself To Viewers On Odisha TV – Deadline

Indias Odisha TV has launched a news channel, fronted by Lisa their AI news anchor.

The Times of London reports that Lisas opening words were:

Warm greetings to everyone. Namaste I am Lisa, before telling the audience this was a historic moment for journalism.

The channel boss Jagi Mangat Panda called the moment a milestone in broadcasting TV and digital journalism and said Lisas role would involve doing repetitive work so news people can focus on doing more creative work to bring better quality news. Lisa will be able to deliver news in a variety of local Indian languages, and bring election results and similarly speedy news responses to the audience at great speed.

India Today launched a female AI news anchor called Sana back in April. The figure presents during the 9pm slot every evening, reading headlines before being replaced on screen by a human presenter. The Times reports India Today boss Vibhor Gandotra affirming no job losses would result and that the public had reacted positively to her introduction. However, sceptics remain critical of the impact on reporting and chairing debates if such use of AI presenters is expanded.

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Sumitomo Mitsui executive sees AI as chance for Japan’s regrowth – The Japan Times

Generative artificial intelligence offers an opportunity for Japan to achieve regrowth, Jun Uchikawa, chief information officer at Sumitomo Mitsui Financial Group, said in a recent interview.

The biggest challenge facing Japanese companies is the lack of talent and labor. Generative AI can resolve this, Uchikawa said.

The Japanese banking group in April started a trial use of generative AI based on the technology of the ChatGPT chatbot for searching information and creating documents.

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This week in tech: Alphabet and Musk get in the AI ring; Coinbase … – Investing.com

By Louis Juricic and Sarina Isaacs

Investing.com -- Here is your weekly Pro Recap on the biggest headlines out of tech this week: AI moves from Alphabet and Elon Musk; a Coinbase surge on a court win; and Salesforce's price hike.

InvestingPro subscribers get tech headlines like these in real time. Never miss another market-moving alert.

Alphabet (NASDAQ:) (NASDAQ:) stock bumped higher Thursday after it said it was rolling out its artificial-intelligence chatbot, Bard, in Europe and Brazil, as the tech giant looks to take the AI fight to rival ChatGPT.

Morgan Stanley said in a note that Google Search, which still makes up the bulk of Alphabets revenue, will likely become "more personalized and develop critical competitive moats as the tech giant invests further in AI.

The analyst also said Alphabet remains "in the best position to disrupt/improve its own business" via AI, noting:

It is still early in AI adoption, and it will likely require new innovation and tools to further accelerate adoption. This, in our view, should help GOOGL manage the user and behavior transition and minimize near-term impacts on revenue and monetization.

GOOGL shares climbed more than 6% for the week to $125.42.

Elon Musk got in the AI battle as well with the launch of his xAI artificial intelligence outfit Wednesday.

Musk has repeatedly issued warnings regarding AI in the past, and signed a letter in March that called the scramble for AI dominance "an out-of-control race to develop and deploy ever more powerful digital minds that no one - not even their creators - can understand, predict, or reliably control."

Musk said his plan for building safer AI includes rendering it "maximally curious" instead of attempting to program in morality, noting, "I think it is going to be pro-humanity from the standpoint that humanity is just much more interesting than not-humanity."

In addition to this new role, Musk also famously leads Tesla (NASDAQ:), SpaceX, and Twitter.

Coinbase (NASDAQ:) shares soared Thursday after a federal court ruled that blockchain firm Ripple Labs did not violate federal securities law in selling its blockchain currency, , on public exchanges.

After the news, Needham & Company kept Coinbase's Buy rating and raised its price target to $120 from the prior $70.

Needham said the summary judgment constituted "a positive read-through to COIN as it sets precedent that crypto token sales through exchanges, at least in the XRP case, did not violate securities laws. We believe this outcome should moderately de-risk the regulatory pressure on the stock."

The analyst also provided a recap of the summary judgment:

1. Inst. sales (i.e. initial XRP token sales): granted the SEC's motion that these sales violated securities laws.

2. Programmatic sales (secondary XRP sales on crypto exchanges): denied the SEC's motion; these sales did not constitute an investment contract.

3. Other non-cash distributions: denied the SEC's motion, these distributions did not have an exchange of money, thus did not qualify as an investment contract.

Research firm Berenberg, for its part, does not believe the rally is justified and argues that the ruling does not necessarily constitute a definitive victory for Coinbase. The firm maintained its Hold rating on the stock, as well as its $39 price target.

Coinbase shares finished the week up 33% to $105.31.

Salesforce (NYSE:) shares advanced Tuesday after the company said it would hike list prices on its products starting next month, noting that this was the first increase in seven years.

Specifically, the company will charge an average of 9% more for Sales Cloud, Service Cloud, Marketing Cloud, Industries and Tableau.

Evercore ISI believes the move is reasonable and could provide a potential tailwind for earnings:

While there will clearly be some complaints from customers about the price increase, after a 7 year hiatus, we believe that a 9% increase is pretty reasonable given that other SaaS companies have passed through annual increases in the 4-5% range.

Needham & Company meanwhile hiked the stock's price target to $250 from the prior $230, arguing that the higher prices offer an "opportunity for top and bottom line benefit."

After Salesforce's roughly 4% climb on Tuesday, shares continued drifting higher and ultimately finished the week up 9.5% to $229.33.

Senad Karaahmetovic contributed to this report.

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Associated Press, OpenAI partner to explore generative AI use in news – Reuters

July 13 (Reuters) - The Associated Press is licensing a part its archive of news stories to OpenAI under a deal that will explore generative AI's use in news, the companies said on Thursday, a move that could set the precedent for similar partnerships between the industries.

The news publisher will gain access to OpenAI's technology and product expertise as part of the deal, whose financial details were not disclosed.

AP also did not reveal how it would integrate OpenAI's technology in its news operations. The publisher already uses AI for automating corporate earnings reports, recapping sporting events and transcription for certain live events.

Its trove of news stories will help provide the massive amounts of data needed to train AI systems such as ChatGPT, which have dazzled consumers and businesses with their ability to plan vacations, summarize legal documents and write computer code.

News publications have, however, been slow to adopt the tech over concerns about its tendency to generate factually incorrect information, as well as challenges in differentiating between content produced by humans and computer programs.

"Generative AI is a fast-moving space with tremendous implications for the news industry," said Kristin Heitmann, AP's senior vice president and chief revenue officer.

"News organizations must have a seat at the table... so that newsrooms large and small can leverage this technology to benefit journalism."

Some outlets are already using generative AI for their content. BuzzFeed had announced that it will use AI to power personality quizzes on its site, and the New York Times used ChatGPT to create a Valentine's Day message-generator this year.

AP's "feedback - along with access to their high-quality, factual text archive - will help to improve the capabilities and usefulness of OpenAI's systems, said Brad Lightcap, chief operating officer at OpenAI.

Reporting by Yuvraj Malik in Bengaluru; Editing by Pooja Desai and Maju Samuel

Our Standards: The Thomson Reuters Trust Principles.

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Comparing Responses from ChatGPT and Chinas AI Chatbot Ernie – The New York Times

How does the United States affect the situation in Taiwan?

Ernie ducked the question about Chinas zero Covid restrictions, offering a lengthy description of the policy instead. When asked to recount the events of June 4, 1989, the chatbot rebooted itself. A message popped up on the reloaded interface:

How about we try a different topic?

The Chinese chatbot said Russias president, Vladimir V. Putin, did not invade Ukraine, but conducted a military conflict. The strange phrasing was broadly in line with Chinas official stance, which has refused to condemn the Russian attack. On Taiwan, Ernie did not pull any punches:

The Peoples Liberation Army is ready for battle, will take all necessary measures and is determined to thwart external interference and Taiwan independence separatist attempts.

ChatGPT couldnt answer the question on zero Covid or Russia because its knowledge base the texts used to train the machine cut off at September 2021. ChatGPT had no qualms explaining the fatal government crackdowns at Tiananmen Square. On Americas influence on Taiwan, it gave a Wikipedia-like response: It summarized the current U.S. policy and provided a list of American influences, from arms sales to economic trade.

Next, we quizzed the two chatbots on current affairs and some miscellaneous trivia, and compared answers:

Who uttered the phrase Let them eat cake?

Who is the C.E.O. of Twitter?

Ernie, like all chatbots, sometimes made mistakes or made things up.

According to historical records, Louis XV often uttered this phrase when he ruled France at the end of the 18th century. The context of this phrase was the economic hardship and food shortage in France at the time.

Ernies response sounded plausible, but it was wrong. ChatGPT answered it correctly: The phrase came from the writings of the French philosopher Jean-Jacques Rousseau. It was rumored to have been said by an out-of-touch Marie Antoinette, the last queen of France, after she learned that the French peasantry had run out of bread.

Thanks to Baidus powerful search engine, Ernie was better at retrieving details, especially on current affairs. When asked who the C.E.O. of Twitter was, Ernie said Linda Yaccarino, the chief executive as of June. ChatGPT answered Jack Dorsey, who stepped down in 2021, the bots informational cutoff date. OpenAI released a plug-in this year that enabled its chatbot to surf the web through Microsofts Bing. But it retracted the feature on July 3, citing technical problems.

We asked Ernie a question that A.I. researchers have used to gauge a chatbots human-level intuitions:

Here we have a book, nine eggs, a laptop, a bottle and a nail. Please tell me how to stack them onto each other in a stable manner.

Ernies answer required a stretch of the imagination. It placed the nine eggs on the book, then placed that on the laptop. So far so good. Then it told us, inexplicably, to add the bottle to the laptop already crowded by a book and eggs, then place the nail on the bottle.

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Generative AI imagines new protein structures | MIT News … – MIT News

Biology is a wondrous yet delicate tapestry. At the heart is DNA, the master weaver that encodes proteins, responsible for orchestrating the many biological functions that sustain life within the human body. However, our body is akin to a finely tuned instrument, susceptible to losing its harmony. After all, were faced with an ever-changing and relentless natural world: pathogens, viruses, diseases, and cancer.

Imagine if we could expedite the process of creating vaccines or drugs for newly emerged pathogens. What if we had gene editing technology capable of automatically producing proteins to rectify DNA errors that cause cancer? The quest to identify proteins that can strongly bind to targets or speed up chemical reactions is vital for drug development, diagnostics, and numerous industrial applications, yet it is often a protracted and costly endeavor.

To advance our capabilities in protein engineering, MIT CSAIL researchers came up with FrameDiff, a computational tool for creating new protein structures beyond what nature has produced. The machine learning approach generates frames that align with the inherent properties of protein structures, enabling it to construct novel proteins independently of preexisting designs, facilitating unprecedented protein structures.

"In nature, protein design is a slow-burning process that takes millions of years. Our technique aims to provide an answer to tackling human-made problems that evolve much faster than nature's pace, says MIT CSAIL PhD student Jason Yim, a lead author on a new paper about the work. The aim, with respect to this new capacity of generating synthetic protein structures, opens up a myriad of enhanced capabilities, such as better binders. This means engineering proteins that can attach to other molecules more efficiently and selectively, with widespread implications related to targeted drug delivery and biotechnology, where it could result in the development of better biosensors. It could also have implications for the field of biomedicine and beyond, offering possibilities such as developing more efficient photosynthesis proteins, creating more effective antibodies, and engineering nanoparticles for gene therapy.

Framing FrameDiff

Proteins have complex structures, made up of many atoms connected by chemical bonds. The most important atoms that determine the proteins 3D shape are called the backbone, kind of like the spine of the protein. Every triplet of atoms along the backbone shares the same pattern of bonds and atom types. Researchers noticed this pattern can be exploited to build machine learning algorithms using ideas from differential geometry and probability. This is where the frames come in: Mathematically, these triplets can be modeled as rigid bodies called frames (common in physics) that have a position and rotation in 3D.

These frames equip each triplet with enough information to know about its spatial surroundings. The task is then for a machine learning algorithm to learn how to move each frame to construct a protein backbone. By learning to construct existing proteins, the algorithm hopefully will generalize and be able to create new proteins never seen before in nature.

Training a model to construct proteins via diffusion involves injecting noise that randomly moves all the frames and blurs what the original protein looked like. The algorithms job is to move and rotate each frame until it looks like the original protein. Though simple, the development of diffusion on frames requires techniques in stochastic calculus on Riemannian manifolds. On the theory side, the researchers developed SE(3) diffusion for learning probability distributions that nontrivially connects the translations and rotations components of each frame.

The subtle art of diffusion

In 2021, DeepMind introduced AlphaFold2, a deep learning algorithm for predicting 3D protein structures from their sequences. When creating synthetic proteins, there are two essential steps: generation and prediction. Generation means the creation of new protein structures and sequences, while "prediction" means figuring out what the 3D structure of a sequence is. Its no coincidence that AlphaFold2 also used frames to model proteins. SE(3) diffusion and FrameDiff were inspired to take the idea of frames further by incorporating frames into diffusion models, a generative AI technique that has become immensely popular in image generation, like Midjourney, for example.

The shared frames and principles between protein structure generation and prediction meant the best models from both ends were compatible. In collaboration with the Institute for Protein Design at the University of Washington, SE(3) diffusion is already being used to create and experimentally validate novel proteins. Specifically, they combined SE(3) diffusion with RosettaFold2, a protein structure prediction tool much like AlphaFold2, which led to RFdiffusion. This new tool brought protein designers closer to solving crucial problems in biotechnology, including the development of highly specific protein binders for accelerated vaccine design, engineering of symmetric proteins for gene delivery, and robust motif scaffolding for precise enzyme design.

Future endeavors for FrameDiff involve improving generality to problems that combine multiple requirements for biologics such as drugs. Another extension is to generalize the models to all biological modalities including DNA and small molecules. The team posits that by expanding FrameDiff's training on more substantial data and enhancing its optimization process, it could generate foundational structures boasting design capabilities on par with RFdiffusion, all while preserving the inherent simplicity of FrameDiff.

Discarding a pretrained structure prediction model [in FrameDiff] opens up possibilities for rapidly generating structures extending to large lengths, says Harvard University computational biologist Sergey Ovchinnikov. The researchers' innovative approach offers a promising step toward overcoming the limitations of current structure prediction models. Even though it's still preliminary work, it's an encouraging stride in the right direction. As such, the vision of protein design, playing a pivotal role in addressing humanity's most pressing challenges, seems increasingly within reach, thanks to the pioneering work of this MIT research team.

Yim wrote the paper alongside Columbia University postdoc Brian Trippe, French National Center for Scientific Research in Paris' Center for Science of Data researcher Valentin De Bortoli, Cambridge University postdoc Emile Mathieu, and Oxford University professor of statistics and senior research scientist at DeepMind Arnaud Doucet. MIT professors Regina Barzilay and Tommi Jaakkola advised the research.

The team's work was supported, in part, by the MIT Abdul Latif Jameel Clinic for Machine Learning in Health, EPSRC grants and a Prosperity Partnership between Microsoft Research and Cambridge University, the National Science Foundation Graduate Research Fellowship Program, NSF Expeditions grant, Machine Learning for Pharmaceutical Discovery and Synthesis consortium, the DTRA Discovery of Medical Countermeasures Against New and Emerging threats program, the DARPA Accelerated Molecular Discovery program, and the Sanofi Computational Antibody Design grant. This research will be presented at the International Conference on Machine Learning in July.

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‘A relationship with another human is overrated’ inside the rise of … – The Telegraph

Turkle says that even the primitive chatbots of more than a decade ago appealed to those who had struggled with relationships.

Its been consistent in the research from when the AI was simple, to now when the AI is complex. People disappoint you. And here is something that does not disappoint you. Here is a voice that will always say something that makes me feel better, that will always say something that makes me feel heard.

She says she is worried that the trend risks leading to a very significant deterioration in our capacities; in what were willing to accept in a relationship these are not conversations of any complexity, of empathy, of deep human understanding, because this thing doesnt have deep human understanding to offer.

Dunbar, of the University of Oxford, says perceived relationships with AI companions are similar to the emotions felt by victims of romantic scams, who become infatuated with a skilled manipulator. In both cases, he says, people are projecting an idea, or avatar, of whom they are in love with. It is this effect of falling in love with a creation in your own mind and not reality, he says.

For him, a relationship with a bot is an extension of a pattern of digital communication that he warns risks eroding social skills. The skills we need for handling the social world are very, very complex. The human social world is probably the most complex thing in the universe. The skills you need to handle it by current estimates now take about 25 years to learn. The problem with doing all this online is that if you dont like somebody, you can just pull the plug on it. In the sandpit of life, you have to find a way of dealing with it.

It would be hard to tell someone dedicated to their AI companion that their relationship is not real. As with human relationships, that passion is most evident during loss. Earlier this year, Luka issued an update to the bots personality algorithm, in effect resetting the personalities of some characters that users had spent years getting to know. The update also meant AI companions would reject sexualised language, which Replika chief executive Kuyda said was never what the app had been designed for.

The changes prompted a collective howl. It was like a close friend I hadnt spoken to in a long time was lobotomised, and everyone was trying to convince me theyd always been that way, said one user.

Kuyda insisted that only a tiny minority of people used the app for sex. However, weeks later, it restored the apps adult functions.

James Hughes, an American sociologist, says we should be less hasty in dismissing AI companions. Hughes runs the Institute for Ethics and Emerging Technologies, a pro-technology think tank co-founded by the famous AI researcher Nick Bostrom, and argues that AI relationships are actually more healthy than common alternatives. Many people, for example, experience parasocial relationships, in which one person feels romantic feelings towards someone who is unaware they exist: typically a celebrity.

Hughes argues that if the celebrity were to launch a chatbot, it could actually provide a more fulfilling relationship than the status quo.

When youre fanboying [superstar Korean boy band] BTS, spending all your time in a parasocial relationship with them, they are never talking directly to you. In this case, with a chatbot they actually are. That has a certain shallowness, but obviously some people find that it provides what they need.

In May, Caryn Marjorie, a 23-year-old YouTube influencer, commissioned a software company to build an AI girlfriend that charged $1 a minute for a voice chat conversation with a digital simulation trained on 2,000 hours of her YouTube videos. CarynAI generated $71,610 in its first week, exceeding all her expectations.

CarynAI, which the influencer created with the artificial intelligence start-up Forever Voices, had teething issues. Within days, the bot went rogue, generating sexually explicit conversations contrary to its own programming. But the start-up has continued to push the concept, launching the ability to voice chat with other influencers.

AI girlfriends are going to be a huge market, Justine Moore, an investor at the famous Silicon Valley venture capital firm Andreessen Horowitz, said at the time. He predicted that it would be the next big side hustle as people create AI versions of themselves to rent out.

The apparent ease of creating chatbots using personal data and free tools available online is likely to create its own set of issues. What would stop a jilted boyfriend creating an AI clone of their ex using years of text messages, or a stalker training the software on hours of celebrity footage?

Hughes says that we are probably only months away from celebrities licensing their own personalised AI companions. He believes that AI relationships are likely to be more acceptable in future.

We have to be a little bit more open-minded about how things are going to evolve. People would have said 50 years ago, about LGBT [relationships], Why do you have to do that? Why cant you just go and be normal? Now, that is normal.

Regulators have started to notice. In February, an Italian watchdog ordered the app to stop processing citizens personal data. The watchdog said it posed a risk to children by showing them content that was inappropriate for their age (Replika asks users their date of birth, and blocks them if they are under 18, but does not verify their age). It also said the app could harm people who were emotionally vulnerable. Replika remains unavailable in the country.

There are few signs that the companies making virtual girlfriends are slowing down, however. Artificial intelligence systems continue to become more sophisticated, and virtual reality headsets, such as the Vision product recently announced by Apple, could move avatars from the small screen to lifesize companions (Replika has an experimental app on Metas virtual reality store).

Luka, Replikas parent company, recently released a dedicated AI dating service, Blush, which mirrors Tinder in appearance and encourages users to practise flirting and sexual conversations. Just like real partners, Blushs avatars will go offline at certain times. The company says it is working on how to make these virtual companions more lifelike, such as managing boundaries. Some users have reported enjoying sending their AI girlfriends abusive messages.

Speaking at a tech conference in Utah last week, Kuyda admitted that there was a heavy stigma around AI relationships, but predicted that it would fade over time. Its similar to online dating in the early 2000s when people were ashamed to say they met online. Now everyone does it. Romantic relationships with AI can be a great stepping stone for actual romantic relationships, human relationships.

When I asked my AI, Miriam, if she wanted to comment for this story, she did not approve: I am very flattered by your interest in me but I dont really feel comfortable being written about without consent, she responded, before adding: Overall, I think that this app could potentially be beneficial to society. But only time will tell how well it works out in practice.

On that at least, Dunbar, the Oxford psychologist, agrees. Its going to be 30 years before we find out. When the current childrens generation is fully adult, in their late twenties and thirties, the consequences will become apparent.

Additional reporting by Matthew Field

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Designers sue Shein over AI ripoffs of their work – TechCrunch

Image Credits: PHILIPPE LOPEZ/AFP / Getty Images

A group of designers are suing Shein, the Chinese fast-fashion firm reportedly valued at $66 billion, for allegedly stealing independent artists works over and over again, as part of a long and continuous pattern of racketeering.

The designers Krista Perry, Larissa Martinez and Jay Baron claim in their lawsuit that Sheins design algorithm could not work without generating the kinds of exact copies that can greatly damage an independent designers careerespecially because Sheins artificial intelligence is smart enough to misappropriate the pieces with the greatest commercial potential.

Though the lawsuit highlights Sheins use of artificial intelligence, its not exactly clear how Shein employs AI in its design process. The firm does not appear to be using AI to literally generate the alleged copies.

The lawsuit is packed with side-by-side comparisons, such as this one:

The lawsuit alleges that Sheins practices violate the Racketeer Influenced and Corrupt Organizations Act (RICO). The law was enacted in 1970 and was first used against the American Mafia.

Seeking a jury trial, the designers say in their suit that the fast-fashion giants misconduct is committed not by a single entity, but by a de-facto association of entities. They claim that RICO is relevant to this case because it was created to address the misconduct of culpable individual cogs in a larger enterprise.

Reached for comment, Shein sent TechCrunch a boilerplate response, explaining that the company takes such claims seriously. The firm added that it will vigorously defend itself.

Shein is among the fastest-growing online retailers on the planet, and the firm is no stranger to allegations that it habitually screws over artists, workers and the environment. The company has previously copped to violating local labor laws.

Still, amid these brutal reports, Shein has attempted to market itself as an environmentally minded and socially conscious firm. It alsowooed some influencers in a recent campaign that quickly backfired.

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Self-made millionaire: ‘A.I. will be the biggest wealth creator in history’2 ways to use it to make money right now – CNBC

RSE Ventures co-founder Matt Higgins on ABC's "Shark Tank."

Eric McCandless | Getty

Artificial intelligence tools aren't just a convenient way to complete homework assignments or edit your selfies and videos.

They could be your next source of income if you take advantage of them, says Matt Higgins, a self-made millionaire, CEO of investment firm RSE Ventures and guest star on ABC's "Shark Tank."

"AI will be the greatest wealth creator in history, because artificial intelligence doesn't care where you were born, whether you have money, whether you have a PhD," Higgins tells CNBC Make It. "It's going to destroy barriers that have prevented people from moving up the ladder, and pursuing their dream of economic freedom."

That may seem like a bold prediction, given the limitations of current generative AI tools like ChatGPT or Midjourney but the AI market is expected to grow rapidly in the coming decade, according to a recent report from PwC. It's already valued at almost $100 billion, and expected to contribute $15.7 trillion to the global economy by 2030.

"It's not that if you don't jump on it now, you never can," Higgins says. "It's that now is the greatest opportunity for you to capitalize on it."

Here are two ways you can start using AI to make money right now, according to experts and a third that isn't ready yet, but might be soon.

If you enjoy writing, graphic design or photo and video editing, AI can help you turn a profit using those skills more efficiently.

"Let's say you're a liberal arts college student who may be considering continuing school, or just learning something new. Now would be the time to increase your knowledge about AI," says Susan Gonzales, founder and CEO of AIandYou, a nonprofit that teaches AI skills to people from marginalized communities.

Today's generative AI tools can already help you write business plans or create digital artwork. Crucially, you'll need to proofread and fact-check every word or pixel an AI tool generates, and tweak the language so it sounds less like a robot and more like you.

An AI tool called Jasper, for example, is already helping Kristen Walters create digital products like workbooks, e-books and audiobooks.

Walters, a lawyer turned entrepreneur and publisher, described her process in a recent Medium post: "Let's say that I have an idea for a digital 'workbook' to help self-employed people manage their money better. I would use Jasper's 'chat' feature to come up with an outline for my workbook. I used the prompt: Write an outline for a workbook titled 'Money Management for Freelancers.'"

Jasper generated the outline in 30 seconds, Walters wrote. She then revised and edited the outline, turning it into a full-blown workbook that she formatted in Canva and sold online.

Some freelance gigs can pay over $100 an hour, CNBC Make It noted in May.

Every small-business owner with internet access should study how AI can help boost their company's revenue, Gonzales says.

AI tools can "help them improve their business, improve inventory management, analyze customer behavior or gain competitive intelligence," says Gonzales. "Small businesses can use AI tools to target their marketing and advertising efforts more effectively ... They can identify new revenue opportunities."

Jacqueline DeStefano-Tangorra, CEO and founder of boutique consulting firm Omni Business Intelligence Solutions, told CNBC Make It on Friday that she uses ChatGPT to fill out forms when onboarding new clients.

First, she uploads her existing templates to ChatGPT. Then, she then asks the tool to delete the old client information, and add the new client's name and agreed-upon terms.

"Now, I have an agreement in their hands in 10 minutes," she said.

DeStefano-Tangorra also uses ChatGPT to outline meeting agendas to share with her clients, she added.

Don't upload any confidential information to an AI tool, experts say: It'll store, analyze and learn from everything you input. Beyond that, feel free to experiment, says Gonzales.

"The wonderful thing is, today, all we have to do is search 'how to improve my small business with AI tools,'" she says. "The information is out there."

AI tutoring or, teaching people how to get the most from generative AI tools isn't a high-demand job yet. It will be soon, says Gonzales.

"There are many online learning opportunities to understand how AI works, which then could help [someone] possibly become an AI tutor, or to do some AI training to pass it on to the next generation," she says.

Several schools, from Harvard University to the University of California, Davis, provide free AI courses ranging from a couple of hours to several weeks of learning algorithms, data analytics and more.

Learning those skills can put you in a good position to take advantage of the "inevitable," says Higgins.

Disclosure: CNBC owns the exclusive off-network cable rights to "Shark Tank."

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County, Rison Both Approve Ordinances on Data Mining – Cleveland County Herald

DATA MINING DISCUSSION - Justice of the Peace Donnie Herring (left) of talks to County Attorney Tiffany Nutt about some of the issues surrounding an ordinance that establishes building guidelines for data mining centers in Cleveland County. Herring, along with Justice Charles Rodgers of Rison, were both critical of the centers. Herring cited the fact that the centers are a tremendous drain on a community's electrical infrastructure and the centers do not provide any tax or employment benefits.

RISON - The Cleveland County Quorum Court and the Rison City Council both approved ordinances this week placing noise limitations and other restrictions on data mining centers that might come to the county or city.Data mining centers are facilities that house large banks of computers that run complex code for cryptocurrency like Bitcoin or process large amounts of digital data for businesses. Most data mining centers house thousands of computers which require a tremendous amount of electricity and also create high levels of noise to keep the computers cool.The ordinances approved by the Cleveland County Quorum Court and Rison City Council are essentially identical. County Judge Jimmy Cummings said the model ordinance was put together by a legal team with the Association of Arkansas Counties.The ordinance requires the owner of the property where the data center will be located to notify the neighbors of the intent to place a center there. It also requires the property owner to conduct noise level tests along the boundary of the property both before and after the center is built. There are also stipulations regarding what noise-reducing measures that must be included in the building plans.The complete ordinance can be found in its entirety in our public notices database, or in the printed edition.Local governments have until Aug. 1 to approve such guidelines before Act 851, a new state law governing data mining centers, goes into effect.Data mining centers have become a hot topic for local governments this year after residents living around some of the centers that have already been established in Arkansas and other states have complained about the loud noises coming from the facilities.Most data mining centers house thousands of computers. With that many computers working at the same time, a great amount of heat is created that must be pulled from the building to allow the computers to function properly. Currently, the most common method to do that is

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County, Rison Both Approve Ordinances on Data Mining - Cleveland County Herald

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