Lessons on AI-driven marketing at EmTech MIT 2024 – TechTarget
Ethical AI establishes principles for AI development and use, while responsible AI ensures they’re implemented in practice. Learn how the two differ and complement each other. Continue Reading
Financial technology can benefit greatly from AI tools and strategies. But financial services companies looking to adopt AI need to understand the risks too. Continue Reading
AI compliance expert Arnoud Engelfriet shares key takeaways from his book ‘AI and Algorithms,’ describing the EU AI Act’s effects on innovation, risk management and ethical AI. Continue Reading
What happens when you expand the use of AI beyond a circle of experts? To prevent business challenges, leaders must make smart investments in AI tools and training for workers. Continue Reading
Custom enterprise models, open source AI, multimodal — learn about the top AI and machine learning trends for 2024 and how they promise to transform the industry. Continue Reading
The rapid evolution and adoption of AI tools has policymakers scrambling to craft effective AI regulation and laws. Law professor Michael Bennett analyzes what’s afoot in 2024. Continue Reading
As businesses in the construction industry integrate AI and machine learning into their processes, the sector’s approach to design, safety and project management is changing. Continue Reading
Unlock the power of AI in data analytics with expert guidance. Learn how to implement AI tools that drive strategic success and future-proof your business. Continue Reading
These risks associated with implementing AI systems must be acknowledged by organizations that want to use the technology ethically and with as little liability as possible. Continue Reading
The growth of generative AI has led to more audio cloning technology. This could affect the U.S. election. Recent incidents show that existing safeguards are not effective. Continue Reading
AI experts expound on these top areas where artificial intelligence technologies can improve enterprise operations and services. Continue Reading
Training data quality and availability aren’t always a given in machine learning projects. When data is limited, costly or nonexistent, few-shot learning can help. Continue Reading
Regression in machine learning helps organizations forecast and make better decisions by revealing the relationships between variables. Learn how it’s applied across industries. Continue Reading
Convolutional and recurrent neural networks have distinct but complementary capabilities and use cases. Compare each model architecture’s strengths and weaknesses in this primer. Continue Reading
As adoption of machine learning grows, companies must become data experts or risk results that are inaccurate, unfair or even dangerous. Here’s how to combat machine learning bias. Continue Reading
Regularization in machine learning refers to a set of techniques used by data scientists to prevent overfitting. Learn how it improves ML models and prevents costly errors. Continue Reading
Compare Anthropic’s Claude vs. OpenAI’s ChatGPT in terms of features, model options, costs, performance and privacy to decide which generative AI tool better suits your needs. Continue Reading
OpenAI’s GPT-4o promises improved multimodal capabilities and increased efficiency. Explore the differences between GPT-4o and its predecessor, GPT-4. Continue Reading
Boosting is a technique used in machine learning that trains an ensemble of so-called weak learners to produce an accurate model, or strong learner. Learn how it works. Continue Reading
Machine learning is changing how we write code, diagnose illnesses and create content, but implementation requires careful consideration to maximize benefits and mitigate risks. Continue Reading
AI- or human-generated? To test their reliability, six popular generative AI detectors were asked to judge three pieces of content. The one they got wrong may surprise you. Continue Reading
Data science and machine learning both play crucial roles in AI, but they have some key differences. Compare the two disciplines’ goals, required skills and job responsibilities. Continue Reading
Although the terms ChatGPT and GPT are both used to talk about generative pre-trained transformers, there are significant technical differences to consider. Continue Reading
What’s the difference between open vs. closed AI, and why are these approaches sparking heated debate? Here’s a look at their respective benefits and limitations. Continue Reading
Although AI can enhance cybersecurity practices like threat detection and vulnerability management, the technology’s limitations ensure a continued need for human security pros. Continue Reading
AI tools and systems are becoming an asset for many real estate endeavors. Explore seven top use cases for AI in the real estate industry and challenges to adoption. Continue Reading
Learn the characteristics of supervised learning, unsupervised learning and semisupervised learning and how they’re applied in machine learning projects. Continue Reading
Building a machine learning model is a multistep process involving data collection and preparation, training, evaluation, and ongoing iteration. Follow these steps to get started. Continue Reading
New features for job applicants, recruiters and businesses include personalized writing suggestions, more advanced search capabilities and AI conversations within LinkedIn Learning. Continue Reading
As AI technology advances, U.S. and international copyright laws are struggling to keep pace, raising legal and ethical questions about ownership and AI-generated content. Continue Reading
Machine learning applications are increasing the efficiency and improving the accuracy of business functions ranging from decision-making to maintenance to service delivery. Continue Reading
Hype around GenAI will inevitably be followed by generative AI disillusionment. Experts ruminate on how to shorten the trough and prepare for the future. Continue Reading
AI is transforming the insurance industry by automating processes and improving risk assessment, but it also poses challenges in data transparency and algorithmic decision-making. Continue Reading
Businesses using AI digital humans in sales and marketing can cut costs through efficiency. However, experts warn of the legal risks and public distrust of the technology. Continue Reading
At the MIT Sloan CIO Symposium, enterprise leaders grappled with AI’s benefits and risks, emphasizing the need for cross-team collaboration, security controls and responsible AI. Continue Reading
At the MIT Sloan CIO Symposium, industry leaders shared experiences with generative AI’s benefits and challenges, highlighting the technology’s ability to assist human workers. Continue Reading
As AI and machine learning become increasingly popular in enterprises, organizations need to learn how to set their initiatives up for success. These MLOps best practices can help. Continue Reading
As AI becomes increasingly widespread, viewpoints featuring both sensationalism and real concern are shaping discussions about the technology and its implications for the future. Continue Reading
By combining specialized models to handle complex tasks, mixture-of-experts architectures can improve efficiency and accuracy for large language models and other AI systems. Continue Reading
An industry group including Arm and Intel seeks to increase the number of options in the AI market and decrease developers’ dependence on GPUs. Continue Reading
The technology will be valuable to tech vendors. For users, a return on investment will depend on the applications as well as whether enterprises choose to build or buy their models. Continue Reading
Building explainable and trustworthy AI systems is paramount. To get there, computer scientists Ron Brachman and Hector Levesque suggest infusing common sense into AI development. Continue Reading
As the project management field increasingly embraces AI-powered software, the benefits can help organizations thrive — but only if the risks are properly considered too. Continue Reading
Now in the early stages of development, AI agents using LLMs might one day number in the billions, operate networks of interconnected ecosystems and alter the commercial landscape. Continue Reading
Multimodal generative AI can integrate and interpret multiple data types within a single model, offering enterprises a new way to improve everyday business processes. Continue Reading
To pinpoint risky and dangerous incidents in workplace environments without having to sift through thousands of data points, a manufacturing group turned to Benchmark Gensuite. Continue Reading
Generative technology-fueled deepfakes could interfere with the November election due to ease of use and power of the technology. The outlook for regulation seems dim. Continue Reading
Generative AI tools such as ChatGPT are entering law practices, promising more efficiency and less time spent on rote tasks. But risks remain around accuracy, ethics and privacy. Continue Reading
AI in the enterprise is changing how work is done, but companies must overcome various challenges to derive value from this powerful and rapidly evolving technology. Continue Reading
As the new technology has exploded in other industries, financial organizations are also exploring how they can apply it. However, regulatory requirements hinder fast adoption. Continue Reading
GPUs are often presented as the vehicle of choice to run AI workloads, but the push is on to expand the number and types of algorithms that can run efficiently on CPUs. Continue Reading
Look back on a hectic year in AI and get up to speed for 2024 by catching up on some of TechTarget Editorial’s top AI news stories from the past year. Continue Reading
The boom will persist as enterprises become acclimated to the technology. More enterprises will start using genAI systems and organizations will incorporate governance measures. Continue Reading
Generative AI has joined the ranks of healthcare professionals in early use cases from medical research to patient communications. AI at scale isn’t far behind. Continue Reading
With the generative AI explosion comes a new trend for the tech giants. Instead of buying smaller companies, big cloud vendors are partnering with the startups. Continue Reading
While many fear that the popularity of large language models could lead to job loss and replacement, some industries such as finance and education are using AI to augment workers. Continue Reading
Introduced in 2017, transformers were a breakthrough in modeling language that enabled generative AI tools such as ChatGPT. Learn how they work and their uses in enterprise settings. Continue Reading
To get the most out of large language models, developers and other users rely on prompt engineering techniques to achieve their desired output. Review 8 tools that can help. Continue Reading
At EmTech MIT, experts explored the challenges and benefits of adopting generative AI in the enterprise, including the pros and cons of open source generative AI models. Continue Reading
GenAI power requirements, the cost of computing and storage, and the high salaries demanded by AI specialists make it unlikely enterprises will take a do-it-yourself approach. Continue Reading
In ‘All-In on AI,’ authors Davenport and Mittal explore AI implementation examples from organizations that already made the AI leap with success. Read this book excerpt to learn more. Continue Reading
Text, image and audio generators offer new content creation capabilities, but they raise concerns about originality, ethics and the impact of automation on creative jobs. Continue Reading
AI expert Ronald Kneusel explains how transformer neural networks and extensive pretraining enable large language models like GPT-4 to develop versatile text generation abilities. Continue Reading
In this interview, author Ronald Kneusel discusses his new book ‘How AI Works,’ the recent generative AI boom and tips for those looking to enter the AI field. Continue Reading
Alida gained early access to the foundation model service in June. It found value using Anthropic’s Claude summarization capability within the service. Continue Reading
Custom enterprise generative AI promises security and performance benefits, but successfully developing models requires overcoming data, infrastructure and skills challenges. Continue Reading
Learn how generative AI will affect organizations in terms of capabilities, enterprise workflows and ethics, and how the technology will shape enterprise use cases. Continue Reading
At Generative AI World 2023, various industries convened to explore existing and potential generative AI use cases. Review insights from one company’s implementation experience. Continue Reading
Understanding AI’s full climate impact means looking past model training to real-world usage, but developers can take tangible steps to improve efficiency and monitor emissions. Continue Reading
More than half of IT and business decision-makers said they have generative AI on the near-term adoption track, according to a report from TechTarget’s Enterprise Strategy Group. Continue Reading
In this excerpt from the book ‘Natural Language Processing in Action,’ you’ll walk through the steps of creating a simple chatbot to understand how to start building NLP pipelines. Continue Reading
In this Q&A, ‘Natural Language Processing in Action’ co-author Hobson Lane discusses how to start learning NLP, including benefits and challenges of building your own pipelines. Continue Reading
Longtime trust and safety leader Tom Siegel offers an insider’s view on moderating AI-generated content, the limits of self-regulation and concrete steps to curb emerging risks. Continue Reading
When gauging the success of generative AI initiatives, metrics should be agreed upon upfront and focus on the performance of the model and the value it delivers. Continue Reading
Several standards, tools and techniques are available to help navigate the nuances and complexities in establishing a generative AI ethics framework that supports responsible AI. Continue Reading
In this interview, ‘Designing Machine Learning Systems’ author Chip Huyen shares advice and best practices for building and maintaining ML systems in real-world contexts. Continue Reading
Although machine learning has a lot in common with traditional programming, the two disciplines have several key differences, author and computer scientist Chip Huyen explains. Continue Reading
More vendors are introducing products to assist enterprises and consumers complete mundane tasks. But there’s a need to be strategic and transparent with these products. Continue Reading
With generative AI adoption on the rise, employers are prioritizing creativity and problem-solving alongside technical skills for roles in software development and data science. Continue Reading
Leaving generative AI unchecked risks flooding platforms with disinformation, fraud and toxic content. But proactive steps by companies and policymakers could stem the tide. Continue Reading
Open source AI models have advantages over generative AI services offered by major cloud providers. But enterprises have to weigh the benefits against the costs. Continue Reading
Enterprise Strategy Group’s Jon Brown discusses the latest findings in his newly released report on observability in IT and application infrastructures and integrating AIOps. Continue Reading
What should enterprises make of the recent warnings about AI’s threat to humanity? AI experts and ethicists offer opinions and practical advice for managing AI risk. Continue Reading
Data quality directly influences the success of machine learning models and AI initiatives. But a comprehensive approach requires considering real-world outcomes and data privacy. Continue Reading
From manufacturing to energy and healthcare, edge AI is promising to various industries. It brings data processing and analysis closer to data sources. Continue Reading
AI and automation have become more commonplace across business processes. In the tech industry, for example, the use of both can enhance quality assurance. Continue Reading
The food manufacturer saves time and money by using the startup’s technology to gain insight into what consumers think about products it has released or is considering releasing. Continue Reading
American soccer club Louisville City and the NBA’s Milwaukee Bucks use Conversica to target the most promising leads for their sales teams and drive profit for their organizations. Continue Reading
Industry leaders in manufacturing must understand the challenges posed by ChatGPT and other generative AI technologies to overcome them and reap AI’s benefits. Continue Reading
Convolutional neural networks and generative adversarial networks are both deep learning models but differ in how they work and are used. Learn the ins and outs of CNNs and GANs. Continue Reading
Industry 4.0 is best known for enhancing the manufacturing sector, but the construction industry is another good use case for AI and related tools. Continue Reading
It’s daunting for a business to adopt Industry 4.0 technologies at scale. However, given the added value of automation and process optimization, the benefits can outweigh risks. Continue Reading
Many healthcare clinicians rely on AI when performing daily tasks and see benefits that outweigh the drawbacks. Continue Reading
With 175 billion parameters, GPT-3 is one of the largest and most well-known neural networks available for natural language applications. Learn why people are so pumped about it. Continue Reading
The use of generative AI is taking off across industries. Two popular approaches are GANs, which are used to generate multimedia, and VAEs, used more for signal analysis. Continue Reading
For manufacturing environments to be included in Industry 4.0, they must adopt up-to-date technologies to improve operations. AI should be foremost among them. Continue Reading
The social media app’s new AI chatbot uses the latest OpenAI technology. However, OpenAI’s privacy policy might make it difficult for enterprises to use the large language model. Continue Reading
The startup’s technology is popular among content creators and also bad actors who use it maliciously. But the AI voice platform also raises the issue of what’s real and fake. Continue Reading
Through a partnership with SAP, Obsess integrated the e-commerce platform within its virtual stores to create an interface that engages young consumers. Continue Reading
A national group formed to advance the research and development of AI in the U.S. proposes ways to add more variety among students, educators and researchers studying AI. Continue Reading
The longtime analytics vendor’s latest release addresses the accuracy of artificial intelligence outputs and includes an …
Using AI and ML in a data warehouse gives the whole organization a single source of truth that can align decision making and …
As analytics enters a new era dominated by GenAI, the vendor has named former Salesforce Sales Cloud and Einstein Analytics …
The energy costs of generative AI aren’t front and center in enterprises’ financial calculations. But industry consultants …
California Governor Gavin Newsom took issue with SB 1047’s broad regulation of AI systems without addressing specific concerns …
To ensure an IT project’s long-term success, stakeholders should keep track of certain KPIs to ensure technical debt is as low as…
The database vendor’s new update includes an integration with pgvector that provides users with the vector search capabilities …
The vendor’s latest set of capabilities includes prebuilt applications and automated features aimed at making it easier to use …
Metadata management tools can range from comprehensive packages of many features to masters of a specific niche. Consider 9 of …
Connected worker capabilities are now part of the Plex smart manufacturing platform, designed for manufacturers to address worker…
Oracle unveils new capabilities for AI use cases, smart manufacturing and sustainability for Oracle Cloud SCM applications at …
Communicating effectively about an ERP implementation is a must because of the complexity and stress of the project. Learn what …
All Rights Reserved, Copyright 2018 – 2024, TechTarget
Privacy Policy
Cookie Preferences
Do Not Sell or Share My Personal Information
source
This is a newsfeed from leading technology publications. No additional editorial review has been performed before posting.
