Speech recognition is the inter-disciplinary sub-field of computational linguistics that develops methodologies and technologies that enables the recognition and translation of spoken language into text by computers. It is also known as automatic speech recognition (ASR), computer speech recognition or speech to text (STT). It incorporates knowledge and research in the linguistics, computer science, and electrical engineering fields.Some speech recognition systems require "training" (also called "enrollment") where an individual speaker reads text or isolated vocabulary into the system. The system analyzes the person's specific voice and uses it to fine-tune the recognition of that person's speech, resulting in increased accuracy. Systems that do not use training are called "speaker independent" systems. Systems that use training are called "speaker dependent".Speech recognition applications include voice user interfaces such as voice dialing (e.g. "call home"), call routing (e.g. "I would like to make a collect call"), domotic appliance control, search (e.g. find a podcast where particular words were spoken), simple data entry (e.g., entering a credit card number), preparation of structured documents (e.g. a radiology report), determining speaker characteristics, speech-to-text processing (e.g., word processors or emails), and aircraft (usually termed direct voice input).The term voice recognition or speaker identification refers to identifying the speaker, rather than what they are saying. Recognizing the speaker can simplify the task of translating speech in systems that have been trained on a specific person's voice or it can be used to authenticate or verify the identity of a speaker as part of a security process.From the technology perspective, speech recognition has a long history with several waves of major innovations. Most recently, the field has benefited from advances in deep learning and big data. The advances are evidenced not only by the surge of academic papers published in the field, but more importantly by the worldwide industry adoption of a variety of deep learning methods in designing and deploying speech recognition systems. These speech industry players include Google, Microsoft, IBM, Baidu, Apple, Amazon, Nuance, GoVivace Inc., SoundHound, iFLYTEK many of which have publicized the core technology in their speech recognition systems as being based on deep learning.
Extreme Ultraviolet (EUV) Lithography is an advanced semiconductor manufacturing technology that utilizes extreme ultraviolet light to create highly detailed and minuscule patterns on silicon wafers. In the ever-evolving landscape of semiconductor fabrication, EUV lithography stands out as a cutting-edge solution for producing intricate integrated circuits with sub-nanometer resolutions. This innovative technology plays a pivotal role in enabling the development of smaller nodes and densely packed transistors, addressing the challenges posed by the increasing complexity of integrated circuits. The EUV Lithography market is characterized by its significance in shaping the future of semiconductor manufacturing. With the continuous demand for higher processing capabilities and more efficient electronic devices, EUV lithography emerges as a key driver of innovation. It allows semiconductor manufacturers to overcome the limitations of traditional optical lithography and achieve unparalleled precision in the creation of semiconductor components. The market's trajectory is fueled by the technology's ability to cater to diverse industries, ranging from consumer electronics to data centers, and its crucial role in advancing emerging technologies like artificial intelligence and 5G. As the semiconductor industry embraces the opportunities presented by EUV lithography, the market landscape is poised for continuous growth and transformative advancements in semiconductor fabrication.
amid surging investor interest in artificial intelligence, many companies suddenly tout AI product roadmaps. But finding legit AI stocks that already garner revenue from generative AI, like Microsoft (MSFT) and Nvidia (NVDA), is a challenging endeavor for investors. For many companies — such as Google parent Alphabet (GOOGL) — the rise of generative AI poses both risk and opportunity.
Amid the emergence of generative AI — which can generate text, images, sounds and video — it's a good time to be cautious amid the hype. GOOGL stock recently became ensnared in a controversy over historical responses generated by its AI-powered chatbot.
In general, look for AI stocks that use artificial intelligence to improve products or gain a
AI Boom: NVDA Stock Delivers
A bellwether for AI stocks, chip maker Nvidia reported fourth quarter sales that tripled from a year earlier, beating high expectations. January quarter data center revenue jumped 409% to $18.4 billion. The company indicated momentum from the artificial-intelligence boom remains strong for NVDA stock.
The Nasdaq jumped 43% in 2023, boosted by buzz around AI stocks.
The top artificial intelligence stocks to buy span chipmakers, software companies, cloud-computing service providers and technology giants that utilize AI tools in many applications.
Meanwhile, Microsoft is the biggest investor in startup OpenAI, the leader in gen AI training models. Drama continues to engulf OpenAI. Tech industry maverick Elon Musk is suing OpenAI — which he co-founded — and CEO Sam Altman, accusing them of prioritizing profit over "the benefit of humanity." Also, Musk claims that OpenAI's partnership with Microsoft violates its founding agreement.
Cloud Computing Giants Build AI Businesses
Cloud computing giants Amazon.com (AMZN), Microsoft and Google sell AI services to business customers.
So far, the biggest demand for AI chips has come from cloud computing giants. Nvidia earnings have boomed amid demand for AI chips built into computer servers.
But analysts expect a market for "edge AI" — on-device processing of AI apps to emerge. While "training" AI models is now the biggest market for chipmakers like Nvidia, the market will shift to "inferencing," or running AI applications, in the long run.
Qualcomm (QCOM) aims to build Snapdragon AI chips for Android smartphones and the "internet of things." ARM Holdings (ARM) is another AI chip maker. ARM stock has gained 70% in 2024.
AI Stocks: How Will Apple Fire Back?
However, most enterprise software makers will not monetize gen AI in a material way until late 2024 or 2025, analysts say.
Meanwhile, Apple (AAPL) topped the $3 trillion market valuation mark in 2023 despite having no immediate answer to ChatGPT. That could change in 2024. Some analysts look for an AI upgrade for the IOS mobile operating system.
Also, AI technology uses computer algorithms. The software programs aim to mimic the human ability to learn, interpret patterns and make predictions.
Until recently, machine learning was largely limited to models that processed data to make predictions. The AI models focused on pattern recognition from existing data. Corporate spending on AI projects was modest as companies mulled return on investment.
Now many companies are scrambling to launch generative AI pilot programs. But investors want AI stocks to show progress in boosting revenue as exploratory projects translate into tangible demand.
AI Stocks To Watch By Industry Group
| Company | Symbol | Comp Rating | Industry name | AI angle |
|---|---|---|---|---|
| Nvidia | (NVDA) | 99 | Elec-Semiconductor Fabless | Cloud computing giants buying more chips to train AI models or run AI workloads. Big lead over rival Advanced Micro Devices (AMD). |
| CrowdStrike | (CRWD) | 97 | Computer Software-Security | AI chatbots expected to automate more functions in security-operations centers and reduce the time to detect computer hacking. |
| Arista Networks | (ANET) | 98 | Computer-Networking | Sells computer network switches that speed up communications among racks of computer servers packed into "hyperscale" data centers. With AI growth, internet data centers will need more network bandwidth. |
| Microsoft | 94 | Computer Software-Desktop | Biggest investor in generative AI startup Open AI, whose ChatGPT users require Azure cloud services. Microsoft's business AI assistant, Office 365 Copilot, will have general availability on Nov. 1. | |
| Salesforce | (CRM) | 97 | Computer Software-Enterprise | Integrating conversational AI assistants within the user interfaces of all Salesforce apps. Expected to use a mix of subscription and consumption-based pricing. |
| Amazon.com | (AMZN) | 96 | Retail-Internet | Alexa smart assistant lags in chatbot technology. Cloud computing unit working with OpenAI rivals Anthropic, Hugging Face and Falcon 40B. |
New generative AI models process "prompts," such as internet search queries, that describe what a user wants to get. Generative AI technologies create text, images, video and computer programming code on their own.
Companies will aim to boost productivity by developing customized AI for specific industries. Proprietary company data will be used to train AI models.
AI systems require massive computing power to find patterns and make inferences from large quantities of data. So the race is on to build AI chips for data centers, self-driving cars, robotics, smartphones, drones and other devices.
Foundation Models Boost Artificial Intelligence
One key question for investors is whether tech industry incumbents will be the big generative AI winners. Or, will a new wave of AI startups eventually dominate?
Large language models provide the building blocks to develop applications. LLMs help AI systems understand the way that humans write and speak. Also, LLMs require training data for specific tasks. Companies with access to troves of data hold an edge.
OpenAI is part of a wave of LLM startups that includes AI21 Labs, Anthropic and Cohere. OpenAI reportedly is on track to generate more than $1 billion in revenue over the next year.
However, OpenAI's dominance faces a challenge from open-source LLMs.
Meta Platforms (META) and IBM (IBM) on Dec. 5 joined with 40 other companies and organizations to form the AI Alliance – an industry group that will support open-source AI models versus proprietary systems from OpenAI, Google and others. Members of the AI Alliance include Intel (INTC), Advanced Micro Devices (AMD) and Oracle (ORCL).
For example, Hugging Face is an open-source community that offers tools to enable users to build LLMs. Hugging Face recently raised $235 million in a Series D funding round. Investors included Google, Amazon, Nvidia, Intel, Qualcomm, IBM and Salesforce.
Amazon in September said it would invest up to $4 billion in Anthropic, a rival of OpenAI. Amazon owns a minority stake in Anthropic, which will use Amazon's cloud-computing services.
How Will Software Firms Monetize AI?
Enterprises will spend more than $40 billion worldwide on gen AI solutions in 2024, up 106% from the previous year, forecasts International Data Corp. The forecast includes software, hardware and business/IT services.
Meanwhile, IDC forecasts that the market will hit $151 billion by 2027, growing at an average rate of 86% annually.
Analysts expect Microsoft's business AI assistant, Office 365 Copilot, to boost revenue in 2024. Microsoft introduced higher-than-expected pricing, at $30 monthly per user, for its Copilot AI software tools.
Further, many other software firms are still testing how to monetize AI products, including Salesforce (CRM), ServiceNow (NOW), Adobe (ADBE) and Workday (WDAY).
In addition, Adobe on Sept. 13 announced the commercial availability of its Firefly generative AI tools. Price hikes related to integrating Firefly tools into cloud products took effect Nov. 1.
At its Dreamforce customer conference, Salesforce touted new generative AI initiatives. But the company didn't hold an analyst day to discuss financial goals at the event. UBS models only a 1% revenue boost for CRM stock from generative AI in fiscal 2025, which starts in February.
Meanwhile, cybersecurity firm CrowdStrike Holding (CRWD) announced pricing for its "Charlotte" generative AI upgrade. It will cost $20 annually per endpoint — either a laptop or smartphone user.
Artificial Intelligence Stocks
Venture capitalist Marc Andreessen once observed how "software is eating the world" by remaking industries through automation. In the same way, artificial intelligence is expected to transform software.
For many companies, gaining an edge with AI requires ongoing investments in computing, networking and data-center infrastructure.
Some analysts view computer gear maker Arista Networks (ANET) as a long-term AI play. Internet data centers will need more computing power and network bandwidth to process AI workloads. June-quarter earnings for ANET stock topped expectations.
Meanwhile, Broadcom (AVGO) and Marvell Technologies (MRVL) are other AI chipmakers to watch. While Broadcom expects its AI-related sales to double this year, other parts of its business are slowing down.
Cybersecurity firms also are among AI stocks to watch. They include Palo Alto Networks (PANW) and CrowdStrike and Cloudflare (NET).
As software companies integrate generative AI tools into products, their customers will spend more on software, analysts say. For example, TD Cowen recently estimated in a note to clients that generative AI software spending will boom from $1 billion in 2022 to $81 billion in 2027, representing a 190%, five-year compound annual growth rate.
Artificial Intelligence Venture Funding
Further, venture capital is flowing to AI startups.
Inflection AI recently raised $1.3 billion in a round led by Microsoft and Nvidia. The funding round values Inflection AI at $4 billion. The company's flagship LLM application is Pi, a personal assistant.
Meanwhile, Anthropic on May 23 announced it has raised $450 million in a funding round led by Spark Capital. Google, Salesforce (CRM), Sound Ventures and Zoom Video Communications (ZM) took part in the funding.
Also, Andreessen Horowitz led a $150 million funding round for Character. AI, which now has a valuation of over $1 billion.
Meanwhile, AI startup Adept recently raised $350 million and is also at a valuation of over $1 billion. Adept has studied how humans use computers — from browsing the internet to navigating a complex enterprise software tool — to build an AI model that can turn a text command into sets of actions.
Further, venture capital money also is flowing to many AI chip startups.
Also, Nvidia faces more competition from AI chip startups Cerebras, Sambanova and Graphcore. AI chip startups also include Groq, Hailo Technologies, Kinera, Luminous, Ateris IP and Mythic.
Tech Giants Among Best Artificial Intelligence Stocks
AI usage is exploding in facial and voice recognition technology, medical diagnostics, algorithmic trading, and automated customer-service bots. Meanwhile, tech giants are expanding AI initiatives.
In e-commerce, Amazon plans to add ChatGPT-style search to its online store.
Amazon for years has used AI to customize online retail offerings and recommend products to website visitors. The e-commerce behemoth also uses robotics and AI at its fulfillments centers.
Also, Amazon leverages AI in retail stores.
At the Google I/O 2023 developers event on May 10, Alphabet showcased how generative AI will be integrated into search, maps, Workspace, photos, cloud computing and Android devices. Also, Google unveiled more of its ad strategy amid the emergence of generative AI at Google Marketing Live on May 23.
Further, AI tools are playing a big role in Facebook-parent Meta's legacy business and new initiatives. As it moves into the metaverse, Meta said it has built a new artificial intelligence supercomputer. Called the AI Research Supercluster, the Meta computer uses chips from Nvidia.
Also, Meta on May 18 hosted an "AI infrastructure" event. Meta disclosed plans to build custom AI chips to be used in its data centers. The new Meta Training and Inference Accelerator, or MTIA, is due out in 2025.
Top AI Stocks: Software Market Upside
Meanwhile, generative AI wars are heating up in marketing. Salesforce in March rolled out Einstein GPT, which adds OpenAI's features across its software platform. Also, pilot generative technology will be available first on its Slack messaging tools. Meanwhile, Salesforce has used "Einstein" predictive AI tools since 2016.
In addition, software maker Atlassian (TEAM) announced "Atlassian Intelligence" at a recent user conference. It embeds OpenAI and LLM technology as a foundational element across all the company's cloud products.
Amid a shortage in software engineers, low-code programming tools are making it easier for business units to develop AI applications. For example, DataRobot is part of a new wave of AI startups bringing low-code tools to market.
Snowflake (SNOW) and startups such as Databricks aim to shake up the database market with lightning-fast analysis of "unstructured data" gathered from sensors. For example, one app would be streaming video analysis.
In addition, Databricks announced new contributions to multiple open-source projects at its recent AI Summit.
IT Services Firms Make Acquisitions
Further, artificial intelligence stocks to watch include information-technology services firms such as IBM, Accenture (ACN), and Epam Systems (EPAM). Meanwhile, Accenture has been gobbling up AI startups.
Meanwhile, IBM continues to acquire artificial intelligence companies, including Databand.ai, Turbonomic, ReaQta, MyInvenio and WDG Automation.
However, not every effort succeeds. IBM sold off Watson Health to private equity firm Francisco Partners. Amid the rise of generative AI, IBM aims to rebound with Watson Code Assistant.