Features
Features
Artificial intelligence platforms
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Claude AI vs. ChatGPT: How do they compare?
Wondering whether to use Anthropic's Claude or OpenAI's ChatGPT for your project? Explore how the two stack up against each other in terms of cost, performance and features. Continue Reading
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AI hardware vendors band together to challenge Nvidia
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
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Manufacturing group uses AI for EHS safety compliance
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
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AI regulation: What businesses need to know in 2024
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
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Catch up on the top AI news of 2023
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
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Compare 8 prompt engineering tools
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
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A customer experience provider's take on Amazon Bedrock
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
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The future of generative AI: How will it impact the enterprise?
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
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Supervised vs. unsupervised learning: Experts define the gap
Learn the characteristics of supervised learning, unsupervised learning and semisupervised learning and how they're applied in machine learning projects. Continue Reading
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Former Google exec on how AI affects internet safety
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
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Attributes of open vs. closed AI explained
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
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How to detect AI-generated content
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
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IT observability tool proliferation fuels AIOps deployments
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
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AI existential risk: Is AI a threat to humanity?
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
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Tribe 9 Foods uses digital twin technology from AI startup
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
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Sport teams drive sales leads with an AI digital assistant
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
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Exploring GPT-3 architecture
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
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ElevenLabs and the risks of voice-generating AI
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
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VR platform aims to give retailers entry into the metaverse
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
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How AI can assist industries in environmental protection efforts
While technology for environmental protection isn't a new concept, AI advancements empower businesses to achieve sustainable operations. Continue Reading
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How AI in weather prediction can aid human intelligence
AI and machine learning models are becoming more widely used in climate prediction and disaster preparedness to aid experts without replacing them. Continue Reading
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The creative thief: AI tools creating generated art
AI systems such as OpenAI's Dall-E, Midjourney and Stable Diffusion are used to create striking images. But it can be unclear if the images are inspired by others or stolen. Continue Reading
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Industries leading the way in conversational AI
Learn how companies in vertical markets are using conversational AI and even partnering with AI developers for software that's tailored to their unique business needs. Continue Reading
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National Grid saves $2 million by partnering with AI startup
The gas and electric company used AiDash to realize efficiencies and improve reliability and vegetation management in Massachusetts after a challenging year. Continue Reading
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How businesses can benefit from conversational AI applications
Conversational AI tools have traditionally been limited in scope, but as they become more humanlike, businesses have realized their potential and applied them to more use cases. Continue Reading
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A closer look at what makes the AI tool Dall-E powerful
The language processing tool differs from most chatbots because it has access to specialized data sets. This makes it powerful, but also potentially dangerous. Continue Reading
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AI for video editing: How one startup is doing it
The vendor's Magnifi platform enables enterprises to generate clips from live or prerecorded videos. The platform uses AI and computer vision to create short clips. Continue Reading
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Enterprise hybrid AI use is poised to grow
Hybrid AI is an approach for businesses that combines human insight with machine learning and deep learning networks. Despite certain challenges, experts believe it shows promise. Continue Reading
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How a soccer club uses facial recognition access control
The Los Angeles Football Club began using the Rock, an autonomous access platform, in 2021. Players and staff use the Rock to access facilities without a key system. Continue Reading
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Automated machine learning improves project efficiency
Until recently, machine learning projects had a small chance of success given the amount of time they require. Automated machine learning software speeds up the process. Continue Reading
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AutoML platforms push data science projects to the finish line
Data science projects often have trouble reaching the production phase, but automated machine learning platforms are accelerating data scientists' work to help them come to fruition. Continue Reading
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Interpretability and explainability can lead to more reliable ML
Interpretability and explainability as machine learning concepts make algorithms more trustworthy and reliable. Author Serg Masís assesses their practical value in this Q&A. Continue Reading
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Differentiating between good and bad AI bias
As lawmakers and regulators look at ways to make machine learning models fair, some tech vendors are creating tools that aim to enable enterprises to achieve that purpose. Continue Reading
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How enterprises will use the still-undefined metaverse
Some metaverse systems will affect the future of work and how enterprises operate. However, their impact will be fully seen only after the full meaning of the metaverse is known. Continue Reading
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Piloting machine learning projects through harsh headwinds
To get machine learning projects off the ground and speed deployments, data science teams need to ask questions on a host of issues ranging from data quality to product selection. Continue Reading
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Tips and tricks for deploying TinyML
A typical TinyML deployment has many software and hardware requirements, and there are best practices that developers should be aware of to help simplify this complicated process. Continue Reading
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Cryptocurrency broker uses Ada AI platform for better CX
LiteBit partnered with the customer service vendor in 2017 when the cryptocurrency market was booming. Since then, it has been using the vendor's AI-powered chatbot. Continue Reading
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SambaNova makes a mark in the AI hardware realm
The startup says it is innovating AI hardware systems with its data flow architecture that enterprises can use to be more efficient when processing large AI data sets. Continue Reading
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AI carbon footprint: Helping and hurting the environment
Companies can use AI to help the environment, including by using it to prevent forest fires and reduce factory waste. At the same time, AI has its own carbon footprint. Continue Reading
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Expanding explainable AI examples key for the industry
Improving AI explainability and interpretability are keys to building consumer trust and furthering the technology's success. Continue Reading
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AI and climate change: The mixed impact of machine learning
AI can both help and hurt the environment. While companies use artificial intelligence to increase factory efficiency and lower energy costs, training AI demands a lot of energy. Continue Reading
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Energy consumption of AI poses environmental problems
Data centers and large AI models use massive amounts of energy and are harmful to the environment. Businesses can take action to lower their environmental impact. Continue Reading
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AI accountability: Who's responsible when AI goes wrong?
Who should be held accountable when AI misbehaves? The users, the creators, the vendors? It's not clear, but experts have some ideas. Continue Reading
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Why transparency in AI matters for businesses
To ensure model accuracy, businesses need to understand why their machine learning models make their decisions. Certain tools and techniques can help with that. Continue Reading
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The benefits of an AI-first strategy
Enterprises should put AI first in their business strategies by constantly collecting and using new data to power AI models, argues startup investor Ash Fontana. Continue Reading
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Combating racial bias in AI
By employing a diverse team to work on AI models, using large, diverse training sets, and keeping a sharp eye out, enterprises can root out bias in their AI models. Continue Reading
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10 AI tech trends data scientists should know
The rising environmental and monetary costs of deep learning are catching enterprises' attention, as are new AI techniques like graph neural networks and contrastive learning. Continue Reading
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4 AI career path trajectories for IT professionals
As the desire for AI and machine learning in-house skills skyrocket, those looking to break into the market have a variety of career path options, including AI architect and BI developer. Continue Reading
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Designing and building artificial intelligence infrastructure
Building an artificial intelligence infrastructure requires a serious look at storage, networking and AI data needs, combined with deliberate and strategic planning. Continue Reading
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Addressing 3 infrastructure issues that challenge AI adoption
One of the biggest problems enterprises run into when adopting AI infrastructure is using a development lifecycle that doesn't work when building and deploying AI models. Continue Reading
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How to detect bias in existing AI algorithms
While enterprises can't eliminate bias from their data, they can significantly reduce bias by establishing a governance framework and employing more diverse employees. Continue Reading
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Data scientists vs. machine learning engineers
The positions of data scientist and machine learning engineer are in high demand and are important for enterprises that want to make use of their data and use AI. Continue Reading
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Automatic speech recognition may be better than you think
Even as more enterprises turn to voice recognition systems to process unstructured audio and build virtual assistants, many organizations don't have confidence in the high accuracy of these systems. Continue Reading
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AI voice technology has benefits and limitations
The quality of an automated transcription depends on high-quality recording equipment as well as modern AI-powered transcription software, according to one CTO. Continue Reading
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Mastercard senior VP talks about AI and fraud prevention
Mastercard uses and sells AI-powered technology to prevent fraud and has found that AI-powered services can inspire customer loyalty. Continue Reading
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Steel producer reduces costs using AI in manufacturing
The largest long steel producer in Latin America used data and machine learning predictions to save money, while maintaining the same level of production quality. Continue Reading
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Nvidia acquisition of Arm faces industry, regulatory hurdles
Nvidia's acquisition of Arm Ltd. could change the chipmaker landscape and is reportedly raising industry and regulatory eyebrows. Continue Reading
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Emerging AI startups to look at in 2021
AI startups in the legal, MLOps, NLP and data training markets make this year's list of emerging AI vendors to look out for. Continue Reading
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COVID-19 to drive more AI in retail for small retailers
Retailers were hit hard by the COVID-19 economic fallout, especially small, local businesses. Amid a shift online, AI could help some retailers adjust to the new reality. Continue Reading
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It's been a slow road for AI in oil and gas industries
Analytics and AI can help oil and gas companies better predict supply and demand, involuntary flaring and where to drill. But the companies struggle to get talent. Continue Reading
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AI in operations management relieves pressure on IT teams
AI, when combined with IT operations and DevOps teams, forms AIOps that can greatly improve how IT assets are developed, produced and managed. Continue Reading
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The state of AI in 2020 likely sees more adoption
AI adoption has appeared to grow this year, as organizations deploy automation to augment dwindling workforces and help deal with growing demand during the COVID-19 pandemic. Continue Reading
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Accounts payable automation eliminates invoice backlog
Purple, a mattress company, struggled each week to manually process its myriad invoices and bills. It found relief in automated accounts payable software from a startup vendor. Continue Reading
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AI in sales can make smart lead recommendations
For one B2B sales tech company, a self-service AI startup founded by a former Google employee helps create lead recommendations using machine learning. Continue Reading
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AI in digital transformation vital for enterprises
Without using AI, enterprises will not be able to compete effectively, according to the CEO of Box. Companies need to infuse AI into their digital transformation efforts now. Continue Reading
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7 last-mile delivery problems in AI and how to solve them
Enterprises are discovering it's easier to build AI than it is to integrate it into existing processes. We examine seven 'last-mile' deployment problems when delivering AI. Continue Reading
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Using ModelOps, a financial services company scales out
Using model operations (ModelOps), a fintech startup was able to scale up its model deployment quickly, while also maintaining model governance at scale. Continue Reading
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AI for supply chain can help companies handle disruptions
Even faced with the unpredictability of the coronavirus pandemic, enterprises can generate some stability using AI and machine learning in their supply chains. Continue Reading
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AI in mining takes root in the industry
Executives from data science vendors Kespry and Descartes Labs discuss the importance of AI in the mining industry, a sector that is still fairly new to AI technologies. Continue Reading
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Using automated machine learning for AI in insurance
Using dotData, an automated machine learning vendor, one of the largest insurance firms in Japan built out an AI platform that provides a personalized experience to customers. Continue Reading
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Data Science Central co-founder talks AI, data science trends
In a Q&A, Vincent Granville, executive data scientist and co-founder of Data Science Central, discusses how AI has changed the data science field and the ways in which it will continue to do so. Continue Reading
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Forest fire sensors and AI help detect fires in Chile
Entel Ocean uses DataRobot's automated machine learning platform, as well as IoT sensors, to automatically detect forest fires in Chile. The platform can detect fires faster than manual counterparts. Continue Reading
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Social media marketing vendor uses sentiment analysis
Falcon.io, a social media marketing vendor, turned to AI vendor Lexalytics to add automatic social media sentiment analysis capabilities to its platform. Continue Reading
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GumGum uses machine learning annotation service Figure Eight
Computer vision vendor GumGum gets its training data from Figure Eight, a machine learning training data vendor. Figure Eight uses crowdsourcing to annotate training data. Continue Reading
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AI vendors to watch in 2020 and beyond
The past 10 years have seen a surge of new AI vendors, and the trend isn't likely to end anytime soon, as investors continue to pour money into artificial intelligence. Continue Reading
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How to develop a successful, modern AI infrastructure
Before AI can revolutionize business processes or decision-making, companies need a strong foundation. These tools, platforms and applications help enterprises get started with AI. Continue Reading
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A chemical company simplifies workflows using RPA
Software from Automation Anywhere, an RPA vendor, was easy for Eastman Chemical Company employees to use at a desktop level to automatically handle daily tasks. Continue Reading
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Clearsense uses Unravel Data for AI in performance management
Unravel Data uses AI in performance management to power its APM platform. Clearsense turned to Unravel to get automated optimizations and enable multi-cloud support. Continue Reading
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How to choose the right autoML platform for your enterprise
Before autoML can improve model building and deployment, enterprises need to choose a platform. Here, we evaluate autoML platforms by category, key features and accessibility. Continue Reading
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With ThoughtSpot, GlobalTranz makes AI in logistics platform
GlobalTranz, a logistics company, uses AI and analytics in logistics to predict driver behaviors and plan shipping routes that will keep the shippers and the drivers happy. Continue Reading
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The future of data science and AI points to automatic tools
The relationship between data scientists and companies using AI is evolving rapidly, shifting from a focus on trained professionals to experienced employees with automated tools. Continue Reading
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Analyst, author talks enterprise AI expectations
The author of the upcoming book about enterprise AI talks about realistic AI deployment, dispelling some of the AI hype myths that can be harmful to enterprises. Continue Reading
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Augmented intelligence applications showing ROI, broad success
Enterprise uses have shown that utilizing augmented intelligence technology increases ROI, productivity and linear success as compared to general AI or AGI. Continue Reading
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Agricultural equipment maker uses AI for customer experience
Using AWS services Redshift, S3 and SageMaker, as well as third-party tools, AGCO has created new AI marketing tools and a customer portal to better compete in a tight market. Continue Reading
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Automated transcription services for adaptive applications
NLP technologies have advanced in recent years. Using them, startups have been able to create automatic transcription software for adaptive applications. Continue Reading
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Experts discuss pressing data science problems and solutions
Most data science projects end up facing similar problems, such as lack of robustness and data quality issues. In this feature, experts offer tips on how to overcome these challenges. Continue Reading
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AI acquisitions lead to consolidation
Analytics and AI startups emerge regularly and grow quickly. Frequent acquisitions, however, seem to be creating a more consolidated industry, cementing some vendors at the top. Continue Reading
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AI in pharma: Pfizer team tries Vyasa deep learning platform
To help automatically categorize drug particle shapes, a Pfizer research team is experimenting with Vyasa, a deep learning platform for the life sciences. Continue Reading
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Computer vision tools reach into test, healthcare, security
Gaining a reputation as a viable technology in niche applications like X-ray scans, fingerprint matching and robotics, computer vision looks to mainstream, commodified apps. Continue Reading
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AI at the edge spurs decentralization, IoT interconnectivity
As AI spreads into most enterprises, it's imperative that devices or programs can make immediate smart decisions. Localized AI at the edge is aiming to tackle the lag. Continue Reading
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Reinforcement learning applications provide focused models
Goal-driven AI uses trial-and-error learning methods to find optimal solutions to enterprise problems, while distancing themselves from requiring human maintenance. Continue Reading
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Berklee uses SnapLogic for its AI in higher education needs
Berklee College of Music needed intelligent integration for its two student portals after a merger with the Boston Conservatory. The college chose SnapLogic to connect the systems. Continue Reading
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Better together: Predictive analytics and AI boost each other
Enterprises have long seen the value of predictive analytics, but now that AI is starting to influence forecasting tools, the benefits may start to go even deeper. Continue Reading
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Enterprises are crowdsourcing AI development
By crowdsourcing AI development, enterprises can broaden the knowledge base of their machine learning applications, and early adopters are showing promising results. Continue Reading
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Enterprise AI collaboration tools take tips from dating apps
Enterprise AI collaboration is turning to an unlikely source for inspiration: dating apps that have long used machine-learning based personalization and communication. Continue Reading
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March Madness analytics, AI help data scientist fill bracket
To create his March Madness bracket predictions, the head of data science at DataRobot uses a host of machine learning algorithms and some predictive analytics. Continue Reading
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Data science platforms boost automation, collaboration
Data scientists can choose from a growing list of commercial and open source platforms that ease data access, analytics, model building and management in a collaborative way. Continue Reading
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Researchers race for quantum AI as quantum computing advances
Machine learning is likely to be an early application of quantum computers, as researchers and developers look for the key to a more human-like artificial intelligence. Continue Reading
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AI in accounting boosts compliance and fraud detection
Accounting and finance teams are using AI tools to speed document review and other error-prone processes, which gives a boost to fraud detection and compliance efforts. Continue Reading
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AI for customer experience powers gains at enterprises
Customer experience is growing more central to enterprises' digital strategies, and AI is increasingly driving much of their engagement and retention efforts. Continue Reading