Expert Advice: Page
Practical guidance from industry experts on AI
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Brand Experience Team/TechTarget
The importance and limitations of open source AI models
Despite rising interest in more transparent, accessible AI, a scarcity of public training data and compute infrastructure presents significant hurdles for open source AI projects.
Chris Tozzi • Feb. 7, 2024 -
Brand Experience Team/TechTarget
The role of trusted data in building reliable, effective AI
Without quality data, creating and managing AI systems is an uphill battle. Methods such as zero-copy integration and primary key consistency can ensure trusted data for better AI.
Alan Morrison • Feb. 2, 2024 -
Brand Experience Team/TechTarget
How AI is advancing assistive technology
Recent advances in generative AI could revolutionize assistive technology. For people relying on assistive tools, AI-powered devices could usher in a new era of accessibility.
Mary Pratt • Jan. 22, 2024 -
Brand Experience Team/TechTarget
Explore the impact of data science in business workflows
Data science and machine learning are reshaping business workflows and customer experiences, ushering in an era of highly tailored services and predictive strategies.
Donald Farmer • Jan. 3, 2024 -
Brand Experience Team/TechTarget
How an AI governance framework can strengthen security
Learn how AI governance frameworks promote security and compliance in enterprise AI deployments with essential components such as risk analysis, access control and incident response.
Jerald Murphy • Dec. 14, 2023 -
Brand Experience Team/TechTarget
How to become an MLOps engineer
Explore the key responsibilities and skills needed for a career in MLOps, which focuses on managing ML workflows throughout the model lifecycle.
Stephen Bigelow • Nov. 21, 2023 -
Brand Experience Team/TechTarget
What are the risks and limitations of generative AI?
As enterprise adoption grows, it's crucial for organizations to build frameworks that address generative AI's limitations and risks, such as model drift, hallucinations and bias.
John Burke • Nov. 13, 2023 -
Brand Experience Team/TechTarget
Adversarial machine learning: Threats and countermeasures
As machine learning becomes widespread, threat actors are developing clever attacks to manipulate and exploit ML applications. Review potential threats and how to combat them.
Nihad Hassan • Oct. 30, 2023 -
Brand Experience Team/TechTarget
The data privacy risks of third-party enterprise AI services
Using off-the-shelf enterprise AI can both increase productivity and expose internal data to third parties. Learn best practices for assessing and mitigating data privacy risk.
Chris Tozzi • Oct. 18, 2023 -
Brand Experience Team/TechTarget
How to source AI infrastructure components
Rent, buy or repurpose AI infrastructure? The right choice depends on an organization's planned AI projects, budget, data privacy needs and technical personnel resources.
Chris Tozzi • Oct. 13, 2023 -
Brand Experience Team/TechTarget
Explore 14 real-world use cases for adaptive AI
Adaptive AI's ability to alter its code in response to changing circumstances is useful in dynamic, complex environments. Discover potential business use cases for this technology.
Mary Pratt • Oct. 2, 2023 -
Brand Experience Team/TechTarget
Why and how to use Google Colab
Whether you're looking to gain experience or you're already an expert data scientist, Google Colab can help boost ML and AI initiatives. Follow this tutorial to learn the basics.
John Burke • Sept. 25, 2023 -
Brand Experience Team/TechTarget
Evaluate model options for enterprise AI use cases
To successfully implement AI initiatives, enterprises must understand which AI models will best fit their business use cases. Unpack common forms of AI and best practices.
Tom Nolle • Sept. 18, 2023 -
Brand Experience Team/TechTarget
Assessing the environmental impact of large language models
Large language models like ChatGPT consume massive amounts of energy and water during training and after deployment. Learn how to understand and reduce their environmental impact.
John Burke • Sept. 11, 2023 -
Brand Experience Team/TechTarget
Pros and cons of ChatGPT for finance and banking
While LLMs show promise in the financial industry, responsible implementation requires proceeding with caution. Explore potential use cases and considerations to keep in mind.
George Lawton • July 26, 2023 -
Brand Experience Team/TechTarget
How and why businesses should develop a ChatGPT policy
ChatGPT-like tools have enterprise potential, but also pose risks such as data leaks and costly errors. Establish guardrails to prevent inappropriate use while maximizing benefits.
George Lawton • July 25, 2023 -
Brand Experience Team/TechTarget
Pros and cons of conversational AI in healthcare
Conversational AI platforms have well-documented drawbacks, but if they are regulated and used correctly, they can benefit industries such as healthcare.
John Burke • June 28, 2023 -
Brand Experience Team/TechTarget
How AI can help businesses circumvent inflation
AI can potentially help businesses avoid -- and even counteract -- inflation. Machine learning may be better at this than large language models.
John Burke • June 28, 2023 -
Brand Experience Team/TechTarget
Understand key MLOps governance strategies
Machine learning developers can speed up production of ML applications -- while avoiding risks to their organizations -- with an MLOps governance framework.
John Burke • June 22, 2023 -
Brand Experience Team/TechTarget
Use cases show the combined potential of AI and blockchain
AI and blockchain are both hot topics in IT, yet used for different purposes. However, enterprises across various sectors can now combine both technologies to their advantage.
Jerald Murphy • May 17, 2023 -
Brand Experience Team/TechTarget
How AI can transform industrial safety
AI tools can help ensure workplace safety, from injury detection to VR training. To prevent hazards, business leaders should lean into AI adoption and understand its benefits.
Kashyap Kompella • May 5, 2023 -
Brand Experience Team/TechTarget
Generative AI landscape: Potential future trends
Learn more about the growth of generative AI, its impact on other technologies, use cases and 10 trends that will contribute to the technology's development.
George Lawton • April 19, 2023 -
Brand Experience Team/TechTarget
What do large language models do in AI?
To capitalize on generative AI, business IT leaders must understand the features of large language models.
Johna Johnson • April 4, 2023 -
Brand Experience Team/TechTarget
Why continuous training is essential in MLOps
Organizations with machine learning strategies must consider when evolving data needs require continuous training of ML models.
John Burke • March 16, 2023 -
Brand Experience Team/TechTarget
No- and low-code AI’s role in the enterprise
Low-code tools enable noncoders to build and deploy AI applications. The growing list of these tools ensures that AI development is no longer confined to experts.
Kashyap Kompella • March 9, 2023
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