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Category Archives: Artificial Intelligence

Why Mark Zuckerberg Is the Power Player in Artificial Intelligence – The Motley Fool

Meta Platforms (META 0.24%) will have more GPU power than almost any company in the world by the end of 2024, and the company plans to make most of its AI models open source. This is a powerful strategy that could destroy value for even the biggest competitors in the industry, as Travis Hoium covers in this video.

*Stock prices used were end-of-day prices of Jan. 23, 2024. The video was published on Jan. 23, 2024.

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. John Mackey, former CEO of Whole Foods Market, an Amazon subsidiary, is a member of The Motley Fool's board of directors. Suzanne Frey, an executive at Alphabet, is a member of The Motley Fool's board of directors. Travis Hoium has positions in Alphabet and Snap. The Motley Fool has positions in and recommends Alphabet, Amazon, Meta Platforms, Microsoft, Nvidia, and Oracle. The Motley Fool has a disclosure policy. Travis Hoium is an affiliate of The Motley Fool and may be compensated for promoting its services. If you choose to subscribe through their link they will earn some extra money that supports their channel. Their opinions remain their own and are unaffected by The Motley Fool.

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Making Money with AI: Unleashing the Potential of Artificial Intelligence – Medium

Artificial Intelligence (AI) is not just revolutionizing technology; its also opening up new avenues for making money. This article delves into the ways individuals can leverage AI to create income streams, offering insights and expert advice for those looking to capitalize on this rapidly evolving field.

Explore the diverse ways in which AI can be harnessed for generating income. From automation to data analysis, understand the broad spectrum of opportunities that AI presents for individuals seeking financial success.

Delve into specific niches within the AI landscape that offer lucrative income potential. Whether its AI-driven content creation, virtual assistance, or machine learning applications, discover where your skills and interests align.

Learn about the essential skills required to make money with AI. From programming languages to understanding algorithms, discover how individuals can prepare themselves for the evolving demands of the AI-driven job market.

Explore the world of freelancing in AI. Discover platforms and opportunities where individuals can offer their AI expertise to businesses and individuals in need of AI-driven solutions.

Uncover the potential of developing AI products. From AI-powered applications to specialized software, learn how to create and market products that leverage the capabilities of artificial intelligence.

Explore the role of AI in content creation. From automated writing tools to AI-generated visuals, discover how individuals can monetize their AI-enhanced content creation skills in various industries.

Understand the demand for AI solutions in the business world. Explore how individuals can create tailored AI solutions to address specific business needs, offering consulting or development services.

Delve into the world of AI competitions. Platforms like Kaggle offer opportunities for individuals to showcase their AI prowess and win cash prizes, providing a unique avenue for making money with AI skills.

Uncover the potential of creating educational content around AI. Whether through online courses, tutorials, or webinars, individuals can monetize their AI knowledge by sharing it with aspiring learners.

Q: Do I need a technical background to make money with AI? While a technical background is beneficial, there are opportunities for individuals with varying levels of expertise. Non-technical roles, such as AI consulting or content creation, also exist.

Q: Can I make money with AI without a formal education in the field? Yes, practical experience and skills often carry significant weight in the AI industry. Self-learning, certifications, and real-world projects can contribute to your success.

Q: Are there ethical considerations in AI income opportunities? Yes, ethical considerations are crucial in AI. Individuals should be mindful of the responsible use of AI and stay updated on ethical guidelines in the industry.

Q: How can I stay updated on the latest developments in AI? Engage with online communities, attend webinars, and follow reputable sources in the AI field. Continuous learning is key to staying informed and competitive.

Q: What are the potential risks of monetizing AI knowledge? Potential risks include ethical concerns, ensuring the security of AI solutions, and staying compliant with relevant regulations. Understanding and mitigating these risks is essential for success.

Q: Can I make money with AI as a side hustle? Yes, many AI opportunities can be pursued as a side hustle. Freelancing, content creation, and participating in competitions are examples of flexible AI income avenues.

Embark on the exciting journey of making money with AI, leveraging its transformative capabilities to create income streams. With strategic insights and a commitment to continuous learning, individuals can position themselves for success in the dynamic and lucrative world of AI-driven income.

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Making Money with AI: Unleashing the Potential of Artificial Intelligence - Medium

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3 Artificial Intelligence Stocks to Buy as the Technology Advances in 2024 – InvestorPlace

According to the International Monetary Fund, we are on the brink of a technology revolution spearheaded by artificial intelligence. The technology will boost productivity, accelerate global growth and raise incomes globally. Multiple AI stocks will benefit from this transformation.

Today, businesses are analyzing how they can leverage AI to improve productivity and how it affects the competitive landscape. Already, organizations are using AI in various use cases, such as application development, customer service, pharmaceutical discovery and creative design.

However, to achieve the promise of AI, companies must make significant investments. That starts with the data and models they use. First, organizations are investing in systems to collect, store, manage and access massive data sets. Then, using the right models, they can derive patterns from their data to drive decision-making, customer service and innovation.

Across the artificial intelligence stack, several companies are meeting various needs. From chip companies producing chips for training large language models to companies developing large language models. These AI stocks are at the forefront of this race and will be winners in 2024.

Source: Sundry Photography / Shutterstock.com

As the largest semiconductor foundry, Taiwan Semiconductor Manufacturing (NYSE:TSM) is one of the leading AI stocks. The company is seeing soaring demand as the scramble for AI chips for data centers and edge computing grows. Over the years, many integrated device manufacturers transitioned to fabless designers, cementing Taiwan Semiconductors importance in chip production.

Taiwan Semiconductor has built an unassailable competitive advantage in its process technology. By investing heavily in research and development, it has maintained leadership in node advancement. As a result, it attracts and retains high-quality, fabless customers. For instance, Apple (NASDAQ:AAPL) in mobile chips and Nvidia (NASDAQ:NVDA) in graphic processing units.

Today, the company is producing leading-edge node chips for its AI customers. Competitors have had challenges producing these chips, enabling Taiwan Semi to dominate the market and charge higher prices. Already the firm is producing 3-nanometer chips for Nvidia, Apple and Intel (NASDAQ:INTC) as competitors struggle to catch up.

On January 19, the company released results and issued upbeat guidance. The company is benefitting from cloud service providers upgrading their data centers with chips supporting AI capabilities. Management was optimistic on high-performance computing demand related to AI, forecasting more than 20% revenue growth in 2024.

While AI adoption has been mainly in the data center, it will become ubiquitous, supporting Taiwan Semis growth. Consumer devices such as smartphones and industrial equipment will need AI capabilities, ushering in the next growth cycle.

Source: rafapress / Shutterstock.com

Although it is primarily a social media company, Meta Platforms (NASDAQ:META) has been a player in the AI for a while. Its increased efforts in the field came out of necessity after Apples IDFA changes curtailed user tracking. Faced with diminished advertising accuracy, Meta Platforms pivoted to AI.

Two years later, the company has become one of the top AI stocks. Notably, CEO Mark Zuckerberg has touted AI as the foundation of our discovery engine and our ads business. The company has amassed hundreds of top A.I. researchers and invested in significant computer power to power these systems. These efforts are paying off with impressive results.

In February 2023, it released LLaMA (Large Language Model Meta AI) a foundational large language model. Metas aim was to advance AI research. Then, in July 2023 it released LLaMA 2 for research and commercial use. Impressively, the model outperforms other open-source language models in coding, reasoning, proficiency, and knowledge tests.

Meta has adopted a unique approach, giving away its models for free. By open-sourcing its models, Meta hopes third-party developers will help improve the platform. Like Linux became the open-source operating system, Meta hopes Llama will become integral to building the next generation of AI applications.

Zuckerberg recently committed to developing artificial general intelligence. He pledged to spend heavily on compute infrastructure to support this effort. If Meta Platforms manages to standardize AI development through its open-source models, it will be a key player in the ecosystem. Considering Zuckerbergs focus on winning in AI, it remains one of the top artificial intelligence stocks, and certainly one of the artificial intelligence stocks you should grab.

Source: IgorGolovniov / Shutterstock.com

Googles parent company, Alphabet (NASDAQ:GOOG, NASDAQ:GOOGL), has been derided for losing the AI war to Microsoft (NASDAQ:MSFT). These assessments seem overly pessimistic. The company is an innovator and will prove the doubters wrong.

The search giant has made significant investments in artificial intelligence. The most significant one was the 2014 acquisition of DeepMind. Secondly, Google has been using artificial intelligence in search for a while, even before OpenAI launched ChatGPT.

Moreover, it is introducing products that will integrate generative AI into search. Today, users can rely on Bard for chat-like responses. It is also testing Search Generative Experience and has expanded its features since its May 2023 launch.

One competitive advantage that positions Google to succeed is its high-quality training data. Today, Google has six products with over 2 billion users and 15 products, each with more than 500 million users. This data has been crucial in creating context-aware AI functions. For instance, features such as Smart Compose in Gmail have significantly improved the user experience.

Alphabets leadership among artificial intelligence stocks extends beyond software to hardware, making it one of the best AI stocks. It developed a specialized chip, a Tensor Processing Unit (TPU), specifically for AI applications. Its TPUs and open-source framework, Tensor, power services such as Gmail, Maps and YouTube.

As Google integrates AI into its products, it will see more growth. For example, serving context-rich ads into generative search results will improve ad conversion and monetization. In December 2023, Google released Gemini, its latest and most powerful LLM, proving Alphabet is still in the AI race. Dont count out this technology giant yet; it has the resources to win!

On the date of publication, Charles Munyi did not hold (either directly or indirectly) any positions in the securities mentioned in this article. The opinions expressed in this article are those of the writer, subject to the InvestorPlace.comPublishing Guidelines.

Charles Munyi has extensive writing experience in various industries, including personal finance, insurance, technology, wealth management and stock investing. He has written for a wide variety of financial websites including Benzinga, The Balance and Investopedia.

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3 Artificial Intelligence Stocks to Buy as the Technology Advances in 2024 - InvestorPlace

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The Future of AI: What to Expect in the Next 5 Years – TechTarget

For the first half of the 20th century, the concept of artificial intelligence held meaning almost exclusively for science fiction fans. In literature and cinema, androids, sentient machines and other forms of AI sat at the center of many of science fiction's high-water marks -- from Metropolis to I, Robot. In the second half of the last century, scientists and technologists began earnestly attempting to realize AI.

At the 1956 Dartmouth Summer Research Project on Artificial Intelligence, co-host John McCarthy introduced the phrase artificial intelligence and helped incubate an organized community of AI researchers.

Often AI hype outpaced the actual capacities of anything those researchers could create. But in the last moments of the 20th century, significant AI advances started to rattle society at large. When IBM's Deep Blue defeated chess master Gary Kasparov, the game's reigning champion, the event seemed to signal not only a historic and singular defeat in chess history -- the first time that a computer had beaten a top player -- but also that a threshold had been crossed. Thinking machines had left the realm of sci-fi and entered the real world.

The era of big data and the exponential growth of computational power in accord with Moore's Law has subsequently enabled AI to sift through gargantuan amounts of data and learn how to accomplish tasks that had previously been accomplished only by humans.

The effects of this machine renaissance have permeated society: Voice recognition devices such as Alexa, recommendation engines like those used by Netflix to suggest which movie you should watch next based on your viewing history, and the modest steps taken by driverless cars and other autonomous vehicles are emblematic. But the next five years of AI development will likely lead to major societal changes that go well beyond what we've seen to date.

Speed of life. The most obvious change that many people will feel across society is an increase in the tempo of engagements with large institutions. Any organization that engages regularly with large numbers of users -- businesses, government units, nonprofits -- will be compelled to implement AI in the decision-making processes and in their public- and consumer-facing activities. AI will allow these organizations to make most of the decisions much more quickly. As a result, we will all feel life speeding up.

End of privacy. Society will also see its ethical commitments tested by powerful AI systems, especially privacy. AI systems will likely become much more knowledgeable about each of us than we are about ourselves. Our commitment to protecting privacy has already been severely tested by emerging technologies over the last 50 years. As the cost of peering deeply into our personal data drops and more powerful algorithms capable of assessing massive amounts of data become more widespread, we will probably find that it was a technological barrier more than an ethical commitment that led society to enshrine privacy.

Thicket of AI law. We can also expect the regulatory environment to become much trickier for organizations using AI. Presently all across the planet, governments at every level, local to national to transnational, are seeking to regulate the deployment of AI. In the U.S. alone, we can expect an AI law thicket as city, state and federal government units draft, implement and begin to enforce new AI laws. And the European Union will almost certainly implement its long-awaited AI regulation within the next six to 12 business quarters. The legal complexity of doing business will grow considerably in the next five years as a result.

Human-AI teaming. Much of society will expect businesses and government to use AI as an augmentation of human intelligence and expertise, or as a partner, to one or more humans working toward a goal, as opposed to using it to displace human workers. One of the effects of artificial intelligence having been born as an idea in century-old science fiction tales is that the tropes of the genre, chief among them dramatic depictions of artificial intelligence as an existential threat to humans, are buried deep in our collective psyche. Human-AI teaming, or keeping humans in any process that is being substantially influenced by artificial intelligence, will be key to managing the resultant fear of AI that permeates society.

The following industries will be affected most by AI:

The notion that AI poses an existential risk to humans has existed almost as long as the concept of AI itself. But in the last two years, as generative AI has become a hot topic of public discussion and debate, fear of AI has taken on newer undertones.

Arguably the most realistic form of this AI anxiety is a fear of human societies losing control to AI-enabled systems. We can already see this happening voluntarily in use cases such as algorithmic trading in the finance industry. The whole point of such implementations is to exploit the capacities of synthetic minds to operate at speeds that outpace the quickest human brains by many orders of magnitude.

However, the existential threats that have been posited by Elon Musk, Geoffrey Hinton and other AI pioneers seem at best like science fiction, and much less hopeful than much of the AI fiction created 100 years ago.

The more likely long-term risk of AI anxiety in the present is missed opportunities. To the extent that organizations in this moment might take these claims seriously and underinvest based on those fears, human societies will miss out on significant efficiency gains, potential innovations that flow from human-AI teaming, and possibly even new forms of technological innovation, scientific knowledge production and other modes of societal innovation that powerful AI systems can indirectly catalyze.

Michael Bennett is director of educational curriculum and business lead for responsible AI in The Institute for Experiential Artificial Intelligence at Northeastern University in Boston. Previously, he served as Discovery Partners Institute's director of student experiential immersion learning programs at the University of Illinois. He holds a J.D. from Harvard Law School.

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Hstoday How Artificial Intelligence Can Reshape Homeland Security in 2024 – HS Today – HSToday

The Department of Homeland Security is on a mission to make sure customer experience (CX) permeates through everything the agency does, and artificial intelligence (AI) can help.

As DHS acting secretary Dana Chinell said, Were really here to inject customer experience design, human-centered design, product management, digital services and skills into everything across the department from service delivery to acquisitions and procurement.

One path to success, as DHS IT leaders have outlined in their FY 2024-2028 IT Strategic Plan, is the use of AI to bolster CX efforts and meet IT modernization goals.

AI is a valuable tool for DHS due to the incredible volume of data and information collected, stored, and shared on a daily basis. DHS can use AI to extract actionable insights from these troves of information. In turn, the DHS workforce is better equipped to make informed decisions quickly, so issues are resolved promptly.

The benefits of using AI have already been realized by DHS for specific issues, such as border protection and immigration.

U.S. Citizenship and Immigration Services (USCIS), for example, has started to use AI to deliver service more efficiently through machine learning models that eliminate redundant paperwork by pulling together information from disparate systems.

Another critical use case of AI is its use for research and development, as the Science and Technology Directorate (S&T) has implemented to help the people on the front lines of our homeland security mission, like first responders. S&Ts AI use has fueled efforts including data analysis, imaging, visualization, and predictive analytics to provide more insight into ongoing DHS efforts.

These data-driven insights can also illuminate solutions to key CX challenges, which any agency will encounter as they update and improve their processes. When working to optimize available data, there are three crucial considerations for agency leaders to keep in mind:

DHS will achieve success when it comes to CX goals if it takes a human-centered design (HCD) approach, which places emphasis on feedback and real-time adjustments. When feedback is continually captured and used to inform design, agencies can build and deliver trustworthy, accessible services for all Americans that help them feel heard and understood.

In December, the agency published an update on its Artificial Intelligence Task Force (AITF) which was created earlier in the year to guide the use of AI.

The Task Force collaborated with DHS Components and offices to initiate several pilot projects, including projects based on internet-accessible, commercially available Generative Al/Large Language Models (LLMs) to advance mission capabilities using AI, read the memo. These pilots will support the Departments understanding of the capabilities, limitations, and risks associated with AI while testing potential solutions. The pilots will also provide real-world data and information on how DHS can scale these technologies across the Department.

Its an important step for the agency, as the proper infrastructure must be in place for AI to be truly effective in reshaping how an agency operates. One example, as stated in the update memo, is the work being done by Customs and Border Patrol (CBP), which began establishing infrastructure requirements for developing, deploying, and managing machine learning models. Specifically, agency leaders have been developing operational pipelines and best practices for deploying and operating machine learning and AI models.

The transformation for DHS will not take place overnight. The IT strategic plan is a five-year strategic plan for a reason.

But the agency, working in concert with industrys top technology companies, has the ability to make significant strides very quickly.

That impact will have far-ranging, and incredibly positive, implications for the American people.

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‘Love Machina’ Review: Artificial Intelligence Doc Fails to Ask the Interesting Questions – IndieWire

Bina48, the central figure of the documentary Love Machina, is among the most terrifying film characters of the year. A disembodied head resembling a middle-aged Black woman and powered by artificial intelligence, Bina48 combines a realistic face, dead emotionless eyes, jerky and mechanical head movements, and speech that resembles a voicemail chatbot more than a living being to create an uncanny valley nightmare. But to basically everyone on screen, Bina48 is a dream, a sign of a world where to quote the motto of her makers at the Terasem Movement Life is purposeful. Death is optional. God is technological. Love is essential.

Whether Love Machina agrees with its subjects views about Bina48, and the larger ongoing debates about the ethics of artificial intelligence, is a bit of a mystery even by the time its credits roll. In taking us into the story of the AI, director Peter Sillen opts for a fairly neutral approach that acknowledges some counterarguments and complications, enough that the film cant be called full-throttle AI propaganda. But the failure to take a strong stance either way makes for a boringly ambivalent film, one that fails to either enchant with promises of the future or terrify with warnings of whats to come.

As the title suggests, Love Machina fashions itself as a story of a marriage, though it doesnt dig particularly deeply into the relationship between its central characters. Bina48 is modeled after Bina Rothblatt, the wife of massively successful lawyer, satellite technology and biotechnology entrepreneur, and SiriusXM founder Martine Rothblatt. Married for over 40 years, Martine and Bina are almost oppressively in love (they even give themselves their own ship name, MarBina), and their pet project the Terasem Movement is intended as a gigantic tribute to their bond. Based on (the Rothblatts interpretations of) beloved sci-fi author Octavia Butlers works, the Terasem Movement seeks to find a way to upload peoples consciousness into artificial intelligence, to cheat death and live forever. Bina is essentially the guinea pig for the organizations efforts, her robot doppelganger powered by an algorithm based on her mind file, a virtual upload of the real womans personality and experiences based on a series of rigorous interviews.

The Terasem Movement and its goals raise a lot of obvious philosophical questions, but Love Machina doesnt try to ask them. The Rothblatts and the majority of the people interviewed in the film among them Terasem managing director Bruce Duncan, the Hanson Robotics engineers that developed Bina48, two of the couples children, and a gaggle of assorted artificial intelligence experts dont reveal any negative or contradictory feelings about the rise of AI or undercut the Rothblatts unwavering vision for the future in any way. Fascinating discussions about deaths role in human life, the nature of human consciousness, and the religious implications of living forever beg to be had about Terasems work, but the film doesnt want to start them.

The movie does tip its toes into the most uncomfortable element of the Bina48 story, the fact that a replica of a Black woman was created by a team of (seemingly) all-white people. Love Machina doesnt ignore it, including scenes where the team that created her discuss the difficulties that came from sculpting Black skin after previously making exclusively white male robots. The only person willing to probe deeper into the subject that we see in the film is Stephanie Dinkins, a professor and artist known for her series of videos in which she converses with Bina48. Dinkins, a Black woman who specializes in art exploring artificial intelligence, isnt necessarily anti-AI, but she reveals her discomfort with Bina48 as a representative of a Black woman, one whose code falls short of grasping the social context of her race. Its easily the most interesting discussion that the film has, but one that gets siloed off into a short section rather than meaningfully incorporated into the films discussions of AI at large.

Thats not the only angle of the film that goes unexamined. Frequently, Love Machina comes across as two films in one: a film about a marriage, and a film about the broader world of artificial intelligence. Rather than complement each other, both stories only flatten when paired together. The refusal to take a particularly strong approach to the question of artificial intelligence means theres very little interesting discussion about the topic to be had, and the film runs out of anything to say about Bina48 and its role in the advancement of AI very early on. In the final few minutes of the film, Sillen loses any semblance of focus and takes detours into the worlds of cryogenics and conversations with AI experts unrelated to Bina48, with little sense of how to meaningfully incorporate them into the broader film. All this is presented in a competent but thoroughly visual and editing style, that a few slightly creepy shots of Bina48 aside is content to just float from talking head to coverage without a real sense of style.

The Rothblatts story, presented via archival photos and video interviews done during the process of creating Binas mind file, is a potentially richer text that gets similarly diluted. For a film ostensibly about marriage, the recounting of their love story is painfully surface-level; you never actually know what draws the two into their passionate relationship. There are interesting threads about Martines gender transition and life as a prominent and powerful trans woman and the interracial nature of their family that the movie approaches timidly and fluffily, never adding dimension beyond the basic facts.

Late in the film, its revealed that part of the couples obsession with preventing death comes from the horrifying experience of witnessing one of their children go through a bout of childhood illness. Because the documentary doesnt tell us much about any of these people, the revelation doesnt particularly invite an emotional response. Like a lot of AI art, Love Machina is too fixated on technological advancement to leave any room for real, interesting human feelings.

Love Machina premiered at the 2024 Sundance Film Festival. It is currently seeking distribution.

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'Love Machina' Review: Artificial Intelligence Doc Fails to Ask the Interesting Questions - IndieWire

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