Machine learning platforms
Enterprises need to make smart investments in machine learning platforms. With a range of features and price tags, making the right ML choice can seem like a daunting task. Discover machine learning platform comparison content, information on getting started with machine learning algorithms and best practices to gain the most from ML projects.
Top Stories
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Feature
07 Nov 2024
Hyperparameter tuning techniques to optimize ML models
Hyperparameters play a key role in shaping how machine learning models learn from data. Learn how adjusting these settings can improve model accuracy and performance. Continue Reading
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Tip
16 Oct 2024
How businesses can measure AI success with KPIs
AI KPIs should include direct and indirect metrics. Learn about the standard and generative AI-specific KPIs that will help you gauge the success of your AI projects. Continue Reading
By- Jerald Murphy, Nemertes Research
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21 Apr 2020
4 explainable AI techniques for machine learning models
At its core, AI is a complex modeling process with layers of information. In order to be able to explain the algorithm's decision-making process, start with its input data. Continue Reading
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Feature
14 Apr 2020
5 deep learning model training tips
Deep learning model training requires not only the right amount of data, but the right type of data. Enterprises must be inventive and careful when training their models. Continue Reading
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Feature
31 Mar 2020
Comparing MLaaS providers by cost, UX and ease of use
MLaaS allows companies to add machine learning capabilities without software development. There are still some barriers to entry, however, and providers are not one-size-fits-all. Continue Reading
By- Scott Robinson, New Era Technology
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Feature
27 Mar 2020
Common sense in AI remains elusive
While AI and machine learning have made major improvements and advancements to computers, common sense in AI has proven to be a significant challenge. Continue Reading
By- Kathleen Walch, Cognilytica
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Feature
10 Feb 2020
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
By- Ronald Schmelzer, Cognilytica
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Feature
30 Jan 2020
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
By- Ronald Schmelzer, Cognilytica
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Feature
28 Jan 2020
AI in hiring gets companies more talent, faster
Through processes like automated candidate sourcing and candidate rediscovery, AI sifts through many resumes to find those most suited to a position. Continue Reading
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Tip
06 Jan 2020
AI and machine learning in cybersecurity: Trends to watch
AI and machine learning in cybersecurity are not so much useful to security teams today as they are necessary. Examine cybersecurity automation trends and benefits. Continue Reading
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Feature
31 Dec 2019
The peaks and pitfalls of hyper-personalization marketing
As consumers begin to revolt against unlimited personal data collection and usage, the longevity of hyper-personalized communication may be cut short. Continue Reading
By- Ronald Schmelzer, Cognilytica
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Feature
24 Dec 2019
UX defines chasm between explainable vs. interpretable AI
From deep learning to simple code, all algorithms should be transparent. The frameworks of AI interpretability and explainability aim to make machine learning understandable to humans. Continue Reading
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News
12 Dec 2019
DataRobot acquisition of Paxata adds data prep to AI platform
By buying data prep vendor Paxata, DataRobot plans to fill out its machine learning and AI platform with tools to automate data prep processes and provide an underlying data fabric. Continue Reading
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Feature
18 Nov 2019
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
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Feature
13 Nov 2019
Using small data sets for machine learning models sees growth
While massive data sets allow for easy training, developers are using new techniques to mine and transfer data that allows for training on limited labeled information. Continue Reading
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News
07 Nov 2019
Booz Allen releases Modzy AI platform and marketplace
Booz Allen Hamilton introduced an AI platform and marketplace made for uploading, deploying and managing AI models across a scalable environment. Continue Reading
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Answer
30 Oct 2019
How to create a data set for machine learning with limited data
A shortage of data for machine learning training sets can halt a company's AI development in its tracks. Turning to external sources and hidden data can solve the problem. Continue Reading
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News
30 Oct 2019
Google releases TensorFlow Enterprise for enterprise users
With the new TensorFlow for enterprises, organizations running previous versions of TensorFlow can get long-term support, including security updates and select bug fixes. Continue Reading
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Feature
30 Oct 2019
The importance of AI for fraud prevention
As fraudsters become increasingly more professional and technologically advanced, financial organizations need to rely on products that use AI for to prevent fraud. Continue Reading
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News
17 Oct 2019
SAS analytics platform aided by $1 billion AI investment
The SAS suite of business intelligence products is quickly seeing results from the vendor's $1 billion commitment to AI seven months after the investment was made public. Continue Reading
By- Eric Avidon, Senior News Writer
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News
10 Oct 2019
As more push for explainable AI, companies add features
As businesses demand more explainable AI, vendors such as IBM and DarwinAI are introducing new features to help break down for business users how AI systems work. Continue Reading
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News
02 Oct 2019
Pride and nerves delay AI adoption in the enterprise
A new study shows that AI adoption in the enterprise is slower than it ought to be. Experts point to a lack of education, the need for explainable AI, and even executive pride. Continue Reading
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News
27 Sep 2019
Modular AI can help enterprises apply and understand AI
Modular AI enables customers to deploy AI as it applies to individual use cases, creating a more focused, open, and cheaper overall AI system and strategy. Continue Reading
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25 Sep 2019
Cambridge Consultants demos show uses of AI
At a demo event, Cambridge Consultants highlighted some of the applications of AI with a system that can count TB cells in a sputum sample and a system that can fix image distortion. Continue Reading
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News
09 Aug 2019
IBM interprets machine models with AI Explainability kit
IBM's open source AI Explainability 360 toolkit packages algorithms and training examples to help humans better understand the decision-making process of machine learning models. Continue Reading
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News
06 Aug 2019
HPE buys MapR assets to fuel AI applications
Longtime independent big data vendor MapR goes out of business, selling technology and intellectual property to HPE. The move marks the continuing decline of the Hadoop market. Continue Reading
By- Shaun Sutner, News Director
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Feature
02 Aug 2019
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
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Feature
31 Jul 2019
AI in law enforcement is growing, but needs work
AI for police includes numerous different analytics, machine learning and natural language processing technologies, including facial recognition and automated transcription tools. Continue Reading
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Feature
24 Jul 2019
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
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Feature
12 Jul 2019
GPU analytics speeds up deep learning, other data insights
GPU-based systems have become a popular platform for deep learning applications, and they're now also being used to accelerate analysis of IoT and geospatial data. Continue Reading
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News
20 Jun 2019
New Amax servers aim to accelerate AI and ML workflows
The Amax BrainMax Series servers feature the latest Nvidia RTX GPU accelerator cards for intensive GPU and AI applications and deep learning initiatives. Continue Reading
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News
20 Jun 2019
DataRobot acquisition of ParallelM to enhance AI management
DataRobot machine learning tools should see a boost following the company's acquisition of ParallelM, a startup with tools for deploying, managing and monitoring AI. Continue Reading
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Feature
19 Jun 2019
AI network security tool autonomously does microsegmentation
To ensure network security, a U.S. law firm has turned to automated network microsegmentation vendor Edgewise. The startup uses machine learning to deploy microsegmentation. Continue Reading
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Feature
18 Jun 2019
AI in professional services revolutionizes white-collar jobs
Professional services and consulting firms are adopting AI at a rapid rate, even though these types of jobs, which mainly focus on interpersonal interaction, may not seem like strong targets for automation. Continue Reading
By- Ronald Schmelzer, Cognilytica
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Answer
17 Jun 2019
How to improve candidate matching with AI in HR recruitment
AI in HR recruitment can source talent externally but can also be used to improve internal projects. AI platforms can match qualified existing employees to potential open projects. Continue Reading
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Feature
13 Jun 2019
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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Feature
07 Jun 2019
How pattern matching in machine learning powers AI
Pattern matching may sound like a simple idea, but it's being used to create some highly advanced AI tools, powering everything from image recognition to natural language applications. Continue Reading
By- Ronald Schmelzer, Cognilytica
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News
04 Jun 2019
New Nuxeo AI platform gives enterprises custom models
Nuxeo Insight Cloud is an AI platform that enables an enterprise to use its own data with machine learning models to improve accuracy by being enterprise-specific. Continue Reading
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Feature
16 May 2019
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
By- Ronald Schmelzer, Cognilytica
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Feature
10 May 2019
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
By- Kathleen Walch, Cognilytica
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News
08 May 2019
Google adds Firebase AI tools to make ML mobile dev easier
A new Google Firebase update simplifies machine learning app development. The update is part of a trend of making machine learning more accessible for developers to create and deploy. Continue Reading
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News
07 May 2019
Google's Cloud TPU v2, v3 Pods accelerate ML training
For the first time, Google Cloud TPU Pods are available in public beta, enabling machine learning developers and engineers to more quickly deploy and train models. Continue Reading
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News
25 Apr 2019
Databricks and Microsoft collaboration boosts MLflow tool
Databricks' MLflow gets support from Microsoft and new features, including easier model tracking, as the open source tool prepares for its 1.0 release next month. Continue Reading
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News
17 Apr 2019
Real-time machine learning with Splice Machine's ML Manager
Splice Machine's AI management software ML Manager, shown at Spark + AI Summit 2019, enables users to update their machine learning models with up-to-date data from varied sources. Continue Reading
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Feature
01 Apr 2019
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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Feature
29 Mar 2019
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
By- Kathleen Walch, Cognilytica
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News
27 Mar 2019
Azure Anomaly Detector service spots business data deviations
Microsoft's Anomaly Detector service for Azure applies AI to customers' time-series data sets to find deviations or patterns that suggest problems. But humans still have the final say. Continue Reading
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Feature
08 Mar 2019
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
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News
22 Feb 2019
IBM adds Power to Watson Machine Learning
While they debuted few whiz-bang offerings, IBM did roll out a handful of products that allow users to run AI technologies across more platforms, including Power Systems servers and competitor clouds. Continue Reading
By- Ed Scannell, Freelancer
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Feature
19 Feb 2019
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
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Answer
11 Feb 2019
What are the pros and cons of machine learning in network security?
The predictive nature of machine learning can benefit network security strategies. But it can also benefit those looking to break through secure network barriers. Continue Reading
By- David Jacobs, The Jacobs Group
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Feature
05 Feb 2019
The new AI frontier: Hyperpersonalized automated advertising
AI-powered automated advertising is being utilized to connect consumer to products, leading to more sales. Simply put: Hyperpersonalized content is taking over the ad space. Continue Reading
By- Kathleen Walch, Cognilytica
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Feature
27 Dec 2018
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
By- Kathleen Walch, Cognilytica
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Feature
12 Dec 2018
Knowledge graph applications in the enterprise gain steam
As the maturity of knowledge graphs improves, enterprises are finding new ways to incorporate them into business operations, though stumbling blocks remain. Continue Reading
By- Kathleen Walch, Cognilytica
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Answer
05 Nov 2018
How do machine learning and AI fit into UC monitoring and analytics?
With the use of machine learning and AI in the very early stages in the UC market, our expert looks at their value in UC monitoring and analytics. Continue Reading
By- Tsahi Levent-Levi, BlogGeek.me
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News
22 Oct 2018
Commvault web interface getting a major overhaul
At Commvault Go, the data protection vendor introduced a revamped user interface with machine learning-powered analytics and smarter storage usage reporting. Continue Reading
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Feature
01 Oct 2018
Convert unstructured data to structured data with machine learning
With access to powerful compute power and advances in machine learning, unstructured data is becoming easier and cheaper for businesses to turn into usable sources of insight. Continue Reading
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News
27 Sep 2018
Hitachi analytics sharpens heterogeneous storage management
Upgraded Hitachi Vantara analytics for storage improves visual mapping of application storage and integrates dynamic-cooling IoT technologies from Vigilent. Continue Reading
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News
20 Sep 2018
Credit card giants step up AI fraud detection
While Capital One and Mastercard delve into AI and machine learning to detect credit card fraud, IBM joins the ranks of AI vendors with AI bias detection tools. Continue Reading
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Feature
13 Sep 2018
How to make a wise machine learning platforms comparison
What data sources does it support? Is it easy to use? Does it have automation features? These are just a few questions to ask when making a machine learning platforms comparison. Continue Reading
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Feature
30 Aug 2018
What do businesses do with the top machine learning platforms?
Take a deep dive into machine learning, including decision trees, clustering, reinforced learning, neural networks, as well as supervised and unsupervised machine learning. Continue Reading
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News
13 Aug 2018
O'Reilly machine learning survey: Enterprises aim for maturity
A new survey finds companies are using fairness and bias as metrics to evaluate the success of a machine learning model. Continue Reading
By- Nicole Laskowski, Senior News Director
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Feature
23 Jul 2018
How to find the best machine learning frameworks for you
There's no shortage of open source deep learning tools today, and evaluating them can be a challenge. But there are some primary considerations to keep in mind. Continue Reading
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Feature
19 Jul 2018
At Intuit, machine learning enhances products, CTO says
Intuit's machine learning and AI technology are transforming its many financial software products. CTO Tayloe Stansbury discusses what that means for Intuit. Continue Reading
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03 Jul 2018
Labeled data brings machine learning applications to life
The types of data being collected for analytics use are increasing, but traditional structured data is a good match for machine learning. Gartner's Svetlana Sicular explains why. Continue Reading
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02 Jul 2018
GPU cloud tools take complexity out of machine learning infrastructure
While talk of AI on GPUs is abuzz, actually building a machine learning infrastructure remains a dark art. A startup's PaaS is looking to automate parts of the process. Continue Reading
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News
08 Jun 2018
Databricks platform additions unify machine learning frameworks
Databricks' new products take aim at simplifying machine learning integration -- something that has become increasingly difficult, as the number of tools has multiplied. Continue Reading
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Feature
19 Apr 2018
Getting to machine learning in production takes focus
Bridging the gap between training and production is one of the biggest machine learning development hurdles enterprises face, but some are finding ways to streamline the process. Continue Reading
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News
02 Mar 2018
AI experts advise developers on dev tools
New tools help developers build better, smarter AI apps, as machine learning toolkits have progressed exponentially over the last few years. Continue Reading
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Feature
15 Feb 2018
Big data throws bias in machine learning data sets
AI holds massive potential for good, but it also amplifies negative outcomes if data scientists don't recognize data biases and correct them in machine learning data sets. Continue Reading
By- Bridget Botelho, Editorial Director, News
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Feature
12 Feb 2018
Machine vision makes paper a thing of the past for insurers
The insurance industry is buried in paper-based processes. Former MetLife CIO Gary Hoberman aims to change that with a platform that runs on AI and machine vision. Continue Reading
By- Nicole Laskowski, Senior News Director
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Feature
31 Jan 2018
How to do a machine learning platform comparison
Experts share their top criteria for choosing the right machine learning vendor in a market that has become crowded and confusing in the last couple years. Continue Reading
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Tip
17 Jan 2018
How to use machine learning to build a predictive algorithm
Machine learning is an invaluable tool for solving business problems, but don't jump into it for predictive analytics without understanding these important factors. Continue Reading
By- Bridget Botelho, Editorial Director, News
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Tip
16 Jan 2018
Synthetic data could ease the burden of training data for AI models
Sometimes it's better to manufacture training data for machine learning models than it is to collect it. Continue Reading
By- Nicole Laskowski, Senior News Director
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Feature
15 Jan 2018
Machine learning models require DevOps-style workflows
Big data is driving the use of AI and machine learning. But teams must be swift to embrace DevOps and re-evaluate models, according to Wikibon's James Kobielus. Continue Reading
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Tip
02 Jun 2016
Why machine learning models require a failover plan
Flawed machine learning models lead to failures and user interruptions. Expert Judith Myerson explains the causes for failures and how a failover plan can improve user experience. Continue Reading