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Should You Forget Nvidia and Buy These 2 Artificial Intelligence (AI) Stocks Right Now?

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Nvidia (NVDA 0.75%) has been a no-brainer buy for investors over the past couple of years. The stock has delivered both earnings and stock price performance as demand heated up for its full range of artificial intelligence (AI) products and services — with the star being Nvidia’s AI chips. The company has built its position as AI chip leader by entering the market early and focusing on innovation.

And though Nvidia stock has climbed 1,400% over the past five years, it still has plenty of room to run as the AI boom enters its next phases of growth. But Nvidia isn’t the only attractive AI stock around, and that means other stocks also may help you to score an AI victory. And some might even make more compelling buys than this AI star right now. Should you forget Nvidia and buy the following two AI stocks right now? Let’s find out.

Image source: Getty Images.

The case for Meta Platforms

Meta Platforms (META -0.69%) has made AI its investment priority over the past few years as it developed its own large language model (LLM), Llama, to drive its AI platform. You probably know Meta best for its social media leadership as it owns apps many of us use daily, such as Facebook and WhatsApp — and these apps drive revenue for Meta as advertisers promote their offerings there to reach us.

Llama already has helped Meta advance in AI, powering Meta AI, the world’s most popular AI assistant. The idea is this — and potentially other AI tools — will prompt us to spend more time on Meta’s apps, and advertisers then may aim to spend even more on advertising here. On top of this, Meta aims to lead in the overall development of AI, and success here could be big for the company down the road. Chief executive Mark Zuckerberg recently formed Meta Superintelligence Labs to focus on AI development and has aggressively hired the industry’s top talent.

It’s clear that Meta is well-positioned to lead in this high-growth field, and the company also has the strong financial position — with the ability to allocate as much as $72 billion to capital spending this year — to support its goals. This is thanks to Meta’s social media moat, or competitive advantage — people don’t easily switch as they know most of their contacts probably won’t follow them to a lesser-known platform. And all of this helps Meta’s revenue to continue climbing.

The case for Alphabet

Alphabet (GOOG 0.49%) (GOOGL 0.49%), like Meta, has a strong revenue-driving business, and it’s also based on something most of us use daily. In this case, it’s Google Search, the world’s No. 1 search engine. Alphabet generates revenue by selling advertising opportunities across its Google platform, and it also is bringing in billions of dollars in revenue through Google Cloud, its cloud computing business.

This company has developed its own LLM, Gemini, and this model powers Alphabet’s virtual assistant and is part of a broad range of offerings customers find at Google Cloud — including access to top-performing chips such as those designed by Nvidia. Thanks to AI, Google Cloud is seeing tremendous growth, with sales rising 28% in the latest quarter to more than $12 billion. And this is a profitable business, with operating income surpassing $2 billion in that period.

Alphabet should benefit from AI in two ways: The company has applied AI to its own business — for example, improving search results and even the advertising experience for those customers. And Alphabet is offering AI tools and services through Google Cloud. All of this means AI could represent a huge and long-lasting growth opportunity for Alphabet.

Are these stocks better buys than Nvidia?

It’s clear that all three of these stocks make interesting AI buys, but to decide where to put our money right now, it’s a good idea to take a look at valuation. Here, Nvidia trades at a very reasonable level but still is the priciest of the bunch.

NVDA PE Ratio (Forward) Chart

NVDA PE Ratio (Forward) data by YCharts

Meta is cheaper, but its valuation actually has climbed since the beginning of the year. Alphabet has the best valuation profile of the three: It’s the cheapest in relation to forward earnings estimates and has seen its valuation decline since the start of 2025. All of this means that though you shouldn’t completely forget about Nvidia — or Meta — right now may be the moment to focus on Alphabet and add a few shares of this cheap but promising AI stock to your portfolio.

Suzanne Frey, an executive at Alphabet, 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. Adria Cimino has no position in any of the stocks mentioned. The Motley Fool has positions in and recommends Alphabet, Meta Platforms, and Nvidia. The Motley Fool has a disclosure policy.



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How Capital One drives returns on its AI investments

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That speed has caught many IT executives off guard as techniques that have always worked for them stop working, Andersen adds. “With this absolute velocity, you are seeing the old norms of trying to figure out how much to invest, those are no longer useful tools,” he says. “If you use traditional methods, you just don’t get it.”

Although Andersen agrees that inference pricing has gone down significantly, “the reality is that we are asking for more sophisticated tasks, queries that are perhaps 1,000 times more complicated” today as compared to two years ago, he says.

Capitalizing on cloud and data

When Natarajan joined Capital One in March 2023, ChatGPT was barely four months old. Despite having been used for about 15 years at that point, generative AI didn’t take off in terms of C-suite and board mindshare until OpenAI introduced ChatGPT.



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Artificial Intelligence (AI) Toolkit Market: A Guide

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Artificial Intelligence (AI) Toolkit Market

The Artificial Intelligence (AI) Toolkit Market is estimated to be valued at approximately USD 10.2 billion in 2024 and is projected to reach around USD 58.7 billion by 2033, growing at a CAGR of about 21.3% during the forecast period from 2025 to 2033.

Artificial Intelligence (AI) Toolkit Market Overview

The Artificial Intelligence (AI) Toolkit Market is rapidly expanding as organizations across industries adopt AI to enhance automation, analytics, and decision-making. AI toolkits, which include frameworks, libraries, and development environments, enable developers to efficiently build, train, and deploy machine learning models. The growing demand for intelligent applications in sectors such as healthcare, finance, retail, and manufacturing is driving market growth. Cloud-based AI platforms and open-source toolkits like TensorFlow, PyTorch, and Scikit-learn are gaining significant traction due to their scalability and ease of use. Furthermore, investments in AI research and government support for digital transformation are boosting adoption. Despite challenges such as data privacy concerns and skill shortages, the market is expected to maintain strong growth through 2033.

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The report further explores the key business players along with their in-depth profiling

Amazon Web Services (AWS), Google LLC, Microsoft Corporation, IBM Corporation, Intel Corporation, NVIDIA Corporation, Oracle Corporation, H2O.ai, Salesforce, Teradata Corporation.

Artificial Intelligence (AI) Toolkit Market Segments:

By Component

• Software (Frameworks, Libraries, Platforms)

• Services (Training & Support, Consulting, Integration)

By Deployment Mode

• Cloud-Based

• On-Premises

By Technology

• Machine Learning

• Natural Language Processing (NLP)

• Computer Vision

• Deep Learning

By Application

• Data Analytics

• Model Training & Deployment

• Speech Recognition

• Image & Video Processing

• Robotic Process Automation

Report Drivers & Trends Analysis:

The report also discusses the factors driving and restraining market growth, as well as their specific impact on demand over the forecast period. Also highlighted in this report are growth factors, developments, trends, challenges, limitations, and growth opportunities. This section highlights emerging Artificial Intelligence (AI) Toolkit Market trends and changing dynamics. Furthermore, the study provides a forward-looking perspective on various factors that are expected to boost the market’s overall growth.

Competitive Landscape Analysis:

In any market research analysis, the main field is competition. This section of the report provides a competitive scenario and portfolio of the Artificial Intelligence (AI) Toolkit Market’s key players. Major and emerging market players are closely examined in terms of market share, gross margin, product portfolio, production, revenue, sales growth, and other significant factors. Furthermore, this information will assist players in studying critical strategies employed by market leaders in order to plan counterstrategies to gain a competitive advantage in the market.

Regional Outlook:

The following section of the report offers valuable insights into different regions and the key players operating within each of them. To assess the growth of a specific region or country, economic, social, environmental, technological, and political factors have been carefully considered. The section also provides readers with revenue and sales data for each region and country, gathered through comprehensive research. This information is intended to assist readers in determining the potential value of an investment in a particular region.

» North America (U.S., Canada, Mexico)

» Europe (Germany, U.K., France, Italy, Russia, Spain, Rest of Europe)

» Asia-Pacific (China, India, Japan, Singapore, Australia, New Zealand, Rest of APAC)

» South America (Brazil, Argentina, Rest of SA)

» Middle East & Africa (Turkey, Saudi Arabia, Iran, UAE, Africa, Rest of MEA)

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➧ What are the market opportunities and threats faced by the vendors in the Artificial Intelligence (AI) Toolkit Market?

➧ What are deals, income, and value examination by types and utilizations of the Artificial Intelligence (AI) Toolkit Market?

➧ What are deals, income, and value examination by areas of enterprises in the Artificial Intelligence (AI) Toolkit Market?

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Contact Us:

Mr. Anurag Tiwari

Email: anurag@omrglobal.com

Contact no: +91 780-304-0404

Website: www.omrglobal.com

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About Orion Market Research

Orion Market Research (OMR) is a market research and consulting company known for its crisp and concise reports. The company is equipped with an experienced team of analysts and consultants. OMR offers quality syndicated research reports, customized research reports, consulting and other research-based services. The company also offers Digital Marketing services through its subsidiary OMR Digital and Software development and Consulting Services through another subsidiary Encanto Technologies.

This release was published on openPR.



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Mapping the application of artificial intelligence in traditional medicine: technical brief – World

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WHO, ITU, WIPO showcase a new report on AI use in traditional medicine

Artificial intelligence (AI) is ushering in a transformative era for traditional medicine, one where centuries-old healing systems are enhanced by cutting-edge technologies to deliver more safe, personalized, effective, and accessible care.

At the AI for Good Global Summit, the World Health Organization (WHO), the International Telecommunication Union (ITU), and the World Intellectual Property Organization (WIPO) released a new technical brief, Mapping the application of artificial intelligence in traditional medicine. Launched under the Global Initiative on AI for Health, this brief offers a roadmap harnessing this potential responsibly while safeguarding cultural heritage and data sovereignty.

A new era for traditional medicine

Traditional, complementary and integrative medicine (TCIM) is practiced in 170 countries and is used by billions of people. The TCIM practices are increasingly popular globally, driven by a growing interest in holistic health approaches that emphasize prevention, health promotion and rehabilitation.

The new brief showcases experiences in many countries using AI to unlock new frontiers in personalized care, drug discovery, and biodiversity conservation. It includes examples such as how AI-powered diagnostics are being used in Ayurgenomics; machine learning models identifying medicinal plants in countries including Ghana and South Africa; and the use of AI to analyze traditional medicine compounds to treat blood disorders in the Republic of Korea.

“Our Global Initiative on AI for Health aims to help all countries benefit from AI solutions and ensure that they are safe, effective, and ethical,” said Seizo Onoe, Director of the ITU Telecommunication Standardization Bureau. “This partnership of ITU, WHO and WIPO brings together the essential expertise.”

Data-driven innovation with ethical roots

The brief emphasizes the importance of good-quality, inclusive data and participatory design to ensure AI systems reflect the diversity and complexity of traditional medicine. AI applications can support strengthening the evidence and research base for TCIM, for example through the Traditional Knowledge Digital Library in India and the Virtual Health Library in the Americas, which use AI to preserve Indigenous knowledge, promote collaboration and prevent biopiracy. Biopiracy is a term for unauthorized extraction of biological resources and/or associated traditional knowledge from developing countries or the patenting of spurious inventions based on such knowledge or resources without compensation.

“Intellectual property is an important tool to accelerate the integration of AI into traditional medicine,” said WIPO Assistant Director- General, Edward Kwakwa. “Our work at WIPO, including the recently adopted WIPO Treaty on Intellectual Property, Genetic Resources and Associated Traditional Knowledge, supports stakeholders manage IP to deliver on policy priorities including for Indigenous Peoples as well as local communities.”

Guarding data sovereignty, empowering communities

The new document calls for urgent action to uphold Indigenous Data Sovereignty (IDSov) and ensure that AI development is guided by free, prior, and informed consent (FPIC) principles. It showcases community-led data governance models from Canada, New Zealand, and Australia, and urges governments to adopt legislation that empowers Indigenous Peoples to control and benefit from their data.

“AI must not become a new frontier for exploitation,” said Dr Yukiko Nakatani, WHO Assistant Director-General for Health Systems. “We must ensure that Indigenous Peoples and local communities are not only protected but are active partners in shaping the future of AI in traditional medicine.”

A global call to action

With the global TCIM market projected to reach nearly US$600 billion in 2025, the application of AI could further accelerate the growth and impact of TCIM and holistic health care. Current utilization and potential of AI highlight many opportunities, but there are many areas of knowledge gaps and risks.

There is a need to develop holistic frameworks tailored to TCIM in areas such as regulation, knowledge sharing, capacity building, data governance and the promotion of equity, to ensure the safe, ethical and evidence-based integration of frontier technologies such as AI into the TCIM landscape.

The new technical brief calls on all stakeholders to:

  • Invest in inclusive AI ecosystems that respect cultural diversity and IDSov;
  • Develop national policies and legal frameworks that explicitly address AI in traditional medicine;
  • Build capacity and digital literacy among traditional medicine practitioners and communities;
  • Establish global standards for data quality, interoperability, and ethical AI use; and
  • Safeguard traditional knowledge through AI-powered digital repositories and benefit-sharing models.

By aligning the power of AI with the wisdom of traditional medicine, a new paradigm of care can emerge; one that honors the past, empowers the present, and shapes a healthier, more equitable future for all.



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