Evaluate

Evaluate

Weigh the pros and cons of technologies, products and projects you are considering.

• How stock market prediction using AI impacts the trading floor

  Robo-advisors and stock monitoring bots are changing the way traders and investors take on the stock market. Continue Reading

• Standards for data sharing should guide AI government regulation

  The White House has taken a deregulatory approach to AI and aims to inspire innovation. An expert weighs in on the role of government in AI and where the industry stands. Continue Reading

• Despite risks, deepfake AI technology has enterprise potential

  The use of GANs to duplicate data has been portrayed as one of AI's biggest potential risks -- but enterprises can also use deepfake technology for positive content production. Continue Reading

• Where are we with machine translation in AI?

  Machine translation has received a boost from cutting-edge technology like deep learning but continues to struggle with the complexities and nuances of human languages. Continue Reading

• Comparing semi-supervised machine learning vs. one-shot learning

  Machine learning models require massive amounts of data -- labeled or unlabeled. Two new approaches are hoping to curtail the need for large data sets and overarching human interference. Continue Reading

• What do NLP benchmarks like GLUE and SQuAD mean for developers?

  AI models for various language understanding tasks have been dramatically improved due to the rise in scale and scope of NLP data sets and have set the benchmark for other models.Continue Reading

• Patience is pivotal for the autonomous vehicle future

  The fatal collision between an Uber ATG vehicle and a pedestrian was a reminder that autonomous vehicles are not ready and that a difficult technological hill remains.Continue Reading

• The uses of AI in medical imaging

  Medical imaging is being deployed with the assistance of AI in order to reduce the strain on medical professionals and hopefully improve patient care.Continue Reading

• Autonomous retail cuts operational costs, personalizes shopping

  Companies are starting to deploy popular AI technologies like RFID, facial recognition and sensor tracking to provide consumers with autonomous shopping experiences.Continue Reading

• Companies focused on building sustainable AI in 2020

  Fewer companies are deploying AI enterprise-wide in 2020 because of universal underestimation of investments and transformation required to have a rounded AI strategy.Continue Reading

• How GE uses a 'Humble AI' approach to manufacturing

  GE executive Colin Parris explains why a deliberate approach to deploying AI is needed when dealing with products that cost hundreds of millions of dollars to make.Continue Reading

• How to build a chatbot with personality and not alienate users

  Adding personality to a chatbot can push it toward the uncanny valley and raises ethical questions. But enterprises can make their bots more engaging, while avoiding these hurdles.Continue Reading

• How Getty Images reduces bias in AI algorithms to avoid harm

  In applications from internal job recruiting to law enforcement technology, AI bias is a widespread issue. Here's what enterprises can do to reduce bias in training and deployment.Continue Reading

• Data visualization process yields 360 AI-driven analytics view

  Data visualization tools find increasing uses as part of AI processes to explore data in the initial stages of model development and make outputs easier to digest.Continue Reading

• Data visualization in machine learning boosts data scientist analytics

  Data scientists offer practical insights into the role of visualization tools in building, exploring, deploying and monitoring their machine learning models.Continue Reading

• Building a better conversational AI assistant requires emotion

  Industry after industry is seeing benefits from chatbot implementation, but customers and developers are looking toward a future of more connected, intelligent conversational agents.Continue Reading

• How the top open source AI software drives innovation

  In the world of AI, open source software is driving most of the innovation. But with vendor tools largely sidelined, what does this mean for things like security and technical support?Continue Reading

• 3 intelligent process automation use cases and how they work

  Enterprises are pursuing intelligent process automation to take their digital transformation and RPA applications to the next level. Here's a look at three use cases.Continue Reading

• Neural network applications in business run wide, fast and deep

  Neural network uses are starting to emerge in the enterprise. This handbook examines the growing number of businesses reporting gains from implementing this technology.Continue Reading

• Deep learning and neural networks gain commercial footing

  Deep learning and neural networks are picking up steam in applications like self-driving cars, radiology image processing, supply chain monitoring and cybersecurity threat detection.Continue Reading

• Ethical concerns of AI call growing adoption into question

  AI tools are getting easier to use every day, putting powerful tools into the hands of potentially malicious users. The time to think about the ethics of AI advances is now.Continue Reading

• Human-AI collaboration produces top results

  Humans and machines have different -- and often complementary -- strengths and weaknesses. That's why we're not seeing automation leading to mass job losses, at least for now.Continue Reading

• How automated machine learning tools pave the way to AI

  Every enterprise is trying to get to machine learning and, ultimately, AI, but not every business has the level of skill in-house to make it happen. Is automated machine learning the answer for them?Continue Reading

• Is artificial general intelligence possible in our lifetime?

  Artificial general intelligence aims to create a wide-reaching, common-sense AI that behaves in a human fashion, but researchers and experts are questioning its plausibility.Continue Reading

• AI gig economy sets workers and bots on collision course

  The future of work has shifted toward a gig economy, with high-value, short-term workers on demand for organizations. The fast turnover and high volume demand AI to reduce friction.Continue Reading

• Clashes between AI and data privacy affect model training

  Enterprises' lax data rules reveal weaknesses around AI and model training -- particularly machine learning's reliance on unrestrained big data collection.Continue Reading

• 5 types of machine learning algorithms you should know

  Machine learning can assist enterprises by quickly modeling large data sets. Choosing the right algorithm depends on the desired outcome and the makeup of your data science team.Continue Reading

• Full benefits of voice assistant tech yet to be realized

  Voice assistant technology is advancing rapidly, thanks to substantial vendor investment. But a new benchmark report reveals the most popular assistants still leave much to be desired.Continue Reading

• 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

• Enterprises work toward AI trust and transparency

  If ignored, a lack of trust in AI algorithms could diminish user adoption. To remedy this risk, enterprises are working to make their applications more transparent and explainable.Continue Reading

• Choosing the right chip foundation for AI-optimized hardware

  Every enterprise is trying to implement AI and machine learning. But, before AI, before clean data and before platform comparison, enterprises need to find the best hardware to support AI.Continue Reading

• 3 GAN use cases that showcase their positive potential

  GANs' ability to create realistic images and deepfakes have caused industry concern. But, if you dig beyond fear, GANs have practical applications that are overwhelmingly good.Continue Reading

• Key considerations for operationalizing machine learning

  Once a machine learning model is trained, developers need to operationalize it. This turns out to be a significant challenge for many enterprises.Continue Reading

• Chatbots in customer service find success with focused goals

  Chatbots can be a great adjunct to customer service, but a successful rollout requires careful planning, flexibility and clear objectives.Continue Reading

• Wayfair takes a dip into NLP image processing technology

  At Wayfair, using computer vision and NLP to understand the meaning behind images and searches is the key to customer recommendation, satisfaction and easy substitutability.Continue Reading

• Causal deep learning teaches AI to ask why

  Most AI runs on pattern recognition, but as any high school student will tell you, correlation is not causation. Researchers are now looking at ways to help AI fathom this deeper level.Continue Reading

• AI for retailers is progressing

  AI in retail adoption has been relatively slow, but it's starting to pick up as retailers see the benefits of AI technologies and the realities of e-commerce competition.Continue Reading

• Use of AI in government makes agencies smarter

  Government agencies are starting to embrace some of the same AI technologies that typical enterprises use, and many are finding increased efficiencies along the way.Continue Reading

• Reinforcement learning and deep learning pairing pushes AI limits

  The pairing of reinforcement and deep learning is enabling researchers to push the boundaries of what AI can do and could help contribute to advanced applications.Continue Reading

• Mapping adoption of artificial intelligence in the enterprise

  As many enterprises focus on use case research, the mature uses of AI are concentrated in supervised learning, structured data extraction and using a small number of platforms.Continue Reading

• Machine learning platform architecture demands deep analysis

  This handbook offers advice on choosing machine learning platforms and using them to get accurate and meaningful information from analytics applications.Continue Reading

• More to machine learning platforms than meets the AI

  To reach full analytics potential, machine learning platforms powered by AI must provide scalability, handle multiple models, integrate with data sources and be cloud-friendly.Continue Reading

• Enterprise consumer relationships are building trust in AI

  Transparency is an increasingly important component of consumer trust. If you want to win over consumers whose data is being collected, start with explainability and collaboration.Continue Reading

• How AI in physical security makes public places safer

  Deep learning-based tools are increasingly finding a home in physical security to enhance the protection of real-world assets and make public spaces safer.Continue Reading

• AI in the legal industry focuses on augmenting research

  From billable time invoice generation to patent attribute data mining, the implementation of AI in law firms has aided in reducing low-value, time-consuming paralegal work.Continue Reading

• Consider these 12 RPA software vendors for deployment

  RPA technology can help companies successfully automate their tasks and processes if they can sift through the options to determine the right system for their enterprise.Continue Reading

• The future of voice assistants is multiturn conversations

  The future looks promising for voice assistants, but for them to really live up to the hype, they are going to have to improve at true multiturn conversations.Continue Reading

• 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

• 5 benefits of AI in the banking industry

  Banks using AI tools are finding the technology can help them overcome traditional customer service challenges, as well as aid in lending decisions and regulatory compliance.Continue Reading

• Natural language processing drives conversational AI trends

  Since the first conversational interfaces, users have desired human-like conversation. Now, AI sentiment analysis, emotion and unique generation are bringing us one step closer.Continue Reading

• Pinpoint the right RPA products to advance your organization

  RPA technology can help organizations cut costs, manage labor and automate tasks. With this buyer's guide on-hand, learn which platform is best for your organization.Continue Reading

• How data privacy and marketing coexist when influencing the public

  The author of a new book on the intersection of advertising and marketing with AI and data privacy talks about influencing the public with technology.Continue Reading

• Applications of autonomous robots lead in the enterprise

  In enterprise AI, bot technology is leading the charge. Seamless integration and process streamlining are initial benefits, but the true profit lies in what comes next -- auto-AI.Continue Reading

• Identify the best RPA tools using these points of consideration

  A successful RPA implementation depends on selecting the proper tool. Learn about the different capabilities and other points of consideration when looking at the options.Continue Reading

• Computer vision AI looks beyond the narrow into the mainstream

  This handbook looks at computer vision in the enterprise, with examples of business applications and advice on deploying systems that incorporate the AI technology.Continue Reading

• 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

• 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

• Inventory optimization machine learning tool sharpens pricing

  Retailers are chasing data-driven process automation in hopes of boosting sales and streamlining margins. But how do you decide which processes to automate or vendor to implement?Continue Reading

• DroneBase uses analytics-powered freelance payment system from Qwil

  DroneBase uses Qwil, vendor of an analytics-based payroll and payments system, to automatically manage and pay the freelance drone pilots who use the DroneBase platform.Continue Reading

• Deep learning recognition use cases grow as tech matures

  As deep learning image and voice recognition technology improves, enterprises are finding novel ways to apply the technology to sharpen and improve their operations.Continue Reading

• Learn the benefits of RPA and the drawbacks by industry

  RPA is a hot IT commodity. Discover more of the benefits (and drawbacks) these tools can usher into organizations and how they can enhance workflows in different industries.Continue Reading

• Top computer vision retail uses and how they enhance shopping

  Computer vision technology can help retailers make shopping in stores faster and easier for customers, while also improving checkout accuracy and theft prevention.Continue Reading

• What is RPA technology and what can it do for your business?

  RPA tools play an important role in modern companies because they can automate manual or repetitive human tasks, freeing workers to focus on more important work.Continue Reading

• Use of AI in payments industry is set to explode

  Payment processors are making wider use of AI technologies as part of an effort to make better use of their vast troves of data and connect more directly with customers.Continue Reading

• Grammarly AI and an update to the writing tool

  A Grammarly update adds a new consistency checker tool to the writing platform that uses AI to automatically scan for multiple writing styles within a single document.Continue Reading

• AI for knowledge management boosts information accessibility

  Integrating AI for knowledge management systems builds intelligent searches. Enterprises benefit from streamlined, smart content platforms that make information accessible.Continue Reading

• Federated deep learning offers new approach to model training

  Training deep learning models puts a massive strain on enterprise infrastructure, but federated learning, which trains models on endpoint devices, could lessen some of the demand.Continue Reading

• 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

• Human-like AI quest drives general AI development efforts

  This guide explores efforts to develop general AI tools with human-like intellectual capabilities and the challenges of creating algorithms that can think like people do.Continue Reading

• How to address the hidden risks of algorithmic decision making

  From biased customer interactions to harmful treatment recommendations, some risks of automated decisions have yet to be resolved. A Wharton School professor has a way out.Continue Reading

• Data preparation for machine learning still requires humans

  Looking to AI to automate more of your processes? Don't overlook the labor that's still needed to prepare data for training machine learning and AI algorithms.Continue Reading

• Data science and machine learning platforms advance analytics

  Data science platforms include a variety of technologies for machine learning and other advanced analytics uses. This handbook examines them and how they can be used.Continue Reading

• 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

• Artificial intelligence creativity tools mimic human ability

  Computational creativity seeks to understand and reproduce facets of human creativity. From songwriting to image creation, artificial intelligence creativity tools are on the rise.Continue Reading

• Enterprises need to develop an AI strategy now

  Business leaders who approach AI as a future concern are likely to miss the boat on this influential technology. The time to explore AI implementation is now.Continue Reading

• Automated machine learning streamlines model building

  Automated machine learning leads to faster model building while democratizing use and increasing implementation. Expert Mike Gualtieri answers major questions about the rising tech.Continue Reading

• Best machine learning platforms comparison and buyer's guide

  Is turning enterprise data into insights a business imperative for you? Then look to machine learning platforms. Here's everything to know about this cutting-edge market.Continue Reading

• AI benefits people, some more than others

  The risks and benefits of AI are not always clear to the average consumer, who might experience the risks more than the benefits, as opposed to the tech giants that create AI.Continue Reading

• Common sense AI approaches point to more general applications

  The race to attain artificial general intelligence is on. Ranging from predictions of 10 to 200 years away, the one thing experts can agree on is that common sense AI is the next step in the journey.Continue Reading

• Perfect AI-defined infrastructure by analyzing your data center

  Before implementing AI, evaluate your IT team and data storage center. Experts explain the fundamental elements of data storage required to tailor an AI-defined infrastructure.Continue Reading

• Natural language processing chatbots bring conversation to AI

  A natural language processing chatbot that focuses on intent can boost the effectiveness of bot technology. By evolving conversationally, bots can become digital coworkers.Continue Reading

• Enterprises using AI in sales gain sharper view of customers

  AI-powered sales tools are helping enterprise sales teams spend less time on tedious administrative tasks and get back to what they do best: selling.Continue Reading

• New uses for GAN technology focus on optimizing existing tech

  GAN technology has emerged as the latest facet of AI that can be applied to existing technology to stack learning. What else can it do? Here are emerging use cases for GANs.Continue Reading

• Interpretable AI has benefits beyond compliance

  Making AI models more interpretable has a wide range of benefits and shouldn't just be thought of as a compliance exercise, experts at the H2O World conference said.Continue Reading

• IBM Think 2019 coverage: Spotlight on data and AI analytics

  This guide compiles news, analysis and trend stories from IBM Think 2019 and before the conference, focusing on IBM's AI, advanced analytics and data management technologies.Continue Reading

• AI regulation stirs as unrestricted AI booms in China

  Governments need to start regulating AI as the technology advances, experts say in part one of a three-part series on AI ethics issues around regulation, control and bias.Continue Reading

• More AI in retail stores means more personalization

  Cheaper and more easily accessible AI developer tools are part of the reason why traditional retailers are better at marketing personalized experiences to customers.Continue Reading

• Recruiting data scientists for AI and machine learning

  When hiring data scientists, be sure to include your data science team in the interview process, and strive to build a data-literate HR department. AI tools may also help.Continue Reading

• New deep learning techniques take center stage

  The days of simple linear regressions for machine learning are giving way to more powerful deep learning techniques that point the way toward general AI capabilities.Continue Reading

• Footasylum drives growth with AI in retail business tools

  AI-driven marketing tools from Peak, an AI and analytics services vendor, has helped apparel seller Footasylum better personalize marketing to customers.Continue Reading

• Using AI for invoices lets ControlExpert add structure to data

  By using Abbyy software and OCR technology, ControlExpert can automatically process and classify millions of structured and unstructured documents and invoices.Continue Reading

• AI for project management makes projects more strategic

  Enterprises are increasingly incorporating AI into their project management processes to make projects more strategic and to make better use of the data created by these processes.Continue Reading

• Agricultural AI yields better crops through data analytics

  The use of agricultural AI optimizes the farming industry by decreasing workloads, analyzing harvesting data and improving accuracy through seasonal forecasting.Continue Reading

• AI in 2019 will be all about bots and pre-trained models

  2019 promises to be a big year for AI, as we're likely to see some trends -- such as adoption of virtual assistants and strong venture capital funding -- continue and others emerge.Continue Reading

• AI winter is coming? Not this time, Tom Davenport says

  A new AI winter, or downturn, is unlikely, even if the current slew of inflated expectations surrounding AI predicts inevitable disappointment, analytics expert Tom Davenport says.Continue Reading

• Davenport: AI-based projects should be focused in scope

  New AI projects in enterprises should focus on achievable goals rather than try to reinvent business processes or products and services, Tom Davenport says.Continue Reading

• The future of AI technology: 2019 and beyond

  Enterprise AI trends in 2019 will likely include more AI-powered tools for healthcare and fintech, as well as accelerating consolidation among smaller AI vendors.Continue Reading

• Explainability is no solution to problem of bias in AI

  Explainability has been touted as a solution to the problem of biased AI models, but experts say that approach only gets you part of the way to bias-free applications.Continue Reading

• 5 trends in AI that shaped 2018

  2018 was a big year in the world of AI. Here we look at five of the leading trends in the use of AI to see how they set the stage for what should be further gains next year.Continue Reading

• Impact of AI on business still more limited than some hoped

  Most businesses have yet to feel the full effect of AI, as enterprises labor to determine where and under what conditions the technology can most effectively be deployed.Continue Reading