- Adversarial Attacks on Explainable AI - Feb 9, 2021.
Are explainability methods black-box themselves?
- 2011: DanNet triggers deep CNN revolution - Feb 4, 2021.
In 2021, we are celebrating the 10-year anniversary of DanNet, which, in 2011, was the first pure deep convolutional neural network (CNN) to win computer vision contests. Read about its history here.
- Adversarial generation of extreme samples - Feb 2, 2021.
In order to mitigate risks when modelling extreme events, it is vital to be able to generate a wide range of extreme, and realistic, scenarios. Researchers from the National University of Singapore and IIT Bombay have developed an approach to do just that.
- Deep Learning Pioneer Geoff Hinton on his Latest Research and the Future of AI - Jan 26, 2021.
Geoff Hinton has lived at the outer reaches of machine learning research since an aborted attempt at a carpentry career a half century ago. He spoke to Craig Smith about his work In 2020 and what he sees on the horizon for AI.
- How to Use MLOps for an Effective AI Strategy - Jan 21, 2021.
The need to deal with the challenges and other smaller nuances of deploying machine learning models has given rise to the relatively new concept of MLOps. – a set of best practices aimed at automating the ML lifecycle, bringing together the ML system development and ML system operations.
- Going Beyond the Repo: GitHub for Career Growth in AI & Machine Learning - Jan 21, 2021.
Many online tools and platforms exist to help you establish a clear and persuasive online profile for potential employers to review. Have you considered how your go-to online code repository could also help you land your next job?
- Top 5 Artificial Intelligence (AI) Trends for 2021 - Jan 21, 2021.
From voice and language driven AI to healthcare, cybersecurity and beyond, these are some of the key AI trends for 2021.
- Top 10 Computer Vision Papers 2020 - Jan 8, 2021.
The top 10 computer vision papers in 2020 with video demos, articles, code, and paper reference.
- 11 Industrial AI Trends that will Dominate the World in 2021 - Jan 7, 2021.
These trends broadly cover the three themes of: Where will businesses adopt AI in 2021? How will AI become more accessible? How will AI capabilities evolve?
- MLOps: Model Monitoring 101 - Jan 6, 2021.
Model monitoring using a model metric stack is essential to put a feedback loop from a deployed ML model back to the model building stage so that ML models can constantly improve themselves under different scenarios.
- 2020: A Year Full of Amazing AI Papers — A Review - Dec 28, 2020.
So much happened in the world during 2020 that it may have been easy to miss the great progress in the world of AI. To catch you up quickly, check out this curated list of the latest breakthroughs in AI by release date, along with a video explanation, link to an in-depth article, and code.
- Production Machine Learning Monitoring: Outliers, Drift, Explainers & Statistical Performance - Dec 21, 2020.
A practical deep dive on production monitoring architectures for machine learning at scale using real-time metrics, outlier detectors, drift detectors, metrics servers and explainers.
- Navigate the road to Responsible AI - Dec 18, 2020.
Deploying AI ethically and responsibly will involve cross-functional team collaboration, new tools and processes, and proper support from key stakeholders.
- Covid or just a Cough? AI for detecting COVID-19 from Cough Sounds - Dec 15, 2020.
Increased capabilities in screening and early testing for a disease can significantly support quelling its spread and impact. Recent progress in developing deep learning AI models to classify cough sounds as a prescreening tool for COVID-19 has demonstrated promising early success. Cough-based diagnosis is non-invasive, cost-effective, scalable, and, if approved, could be a potential game-changer in our fight against COVID-19.
- How The New World of AI is Driving a New World of Processor Development - Dec 14, 2020.
Blaize’s novel stream processor for Edge AI offers a case study of new opportunities for smaller companies to leverage semiconductor industry resources in pursuit of their goals.
- Facebook Open Sources ReBeL, a New Reinforcement Learning Agent - Dec 14, 2020.
The new model tries to recreate the reinforcement learning and search methods used by AlphaZero in imperfect information scenarios.
- Artificial Intelligence in Modern Learning System : E-Learning - Dec 9, 2020.
There has been a considerable shortage in the supply and demand of AI professionals. If you are looking to learn AI or learn machine learning, you can opt for free online courses offered by Great Learning.
- Main 2020 Developments and Key 2021 Trends in AI, Data Science, Machine Learning Technology - Dec 9, 2020.
Our panel of leading experts reviews 2020 main developments and examines the key trends in AI, Data Science, Machine Learning, and Deep Learning Technology.
- AI registers: finally, a tool to increase transparency in AI/ML - Dec 9, 2020.
Transparency, explainability, and trust are pressing topics in AI/ML today. While much has been written about why they are important and what you need to do, no tools have existed until now.
- AI, Analytics, Machine Learning, Data Science, Deep Learning Research Main Developments in 2020 and Key Trends for 2021 - Dec 3, 2020.
2020 is finally coming to a close. While likely not to register as anyone's favorite year, 2020 did have some noteworthy advancements in our field, and 2021 promises some important key trends to look forward to. As has become a year-end tradition, our collection of experts have once again contributed their thoughts. Read on to find out more.
- Roadmaps to becoming a Full-Stack AI Developer, Data Scientist, Machine Learning Engineer, and more - Dec 2, 2020.
As the fields related to AI and Data Science expand, they are becoming complex with more options and specializations to consider. If you are beginning your journey toward becoming an expert in Artificial Intelligence, this roadmap will guide you to find your path along what to learn next while steering clear of the latest hype.
- KDnuggets™ News 20:n45, Dec 2: TabPy: Combining Python and Tableau; Learn Deep Learning with this Free Course from Yann LeCun - Dec 2, 2020.
Combine Python and Tableau with TabPy; Learn Deep Learning with this Free Course from Yann LeCun; Find 15 Exciting AI Project Ideas for Beginners; Read about the Rise of the Machine Learning Engineer; See How to Incorporate Tabular Data with HuggingFace Transformers
- Remembering Pluribus: The Techniques that Facebook Used to Master World’s Most Difficult Poker Game - Dec 1, 2020.
Pluribus used incredibly simple AI methods to set new records in six-player no-limit Texas Hold’em poker. How did it do it?
- 15 Exciting AI Project Ideas for Beginners - Nov 23, 2020.
There are many branches to AI to learn, but a project-based approach can keep things interesting. Here is a list of 15 such projects you can get started on implementing today.
- AI and Automation meets BI - Nov 19, 2020.
Organizations use a variety of BI tools to analyze structured data. These tools are used for ad-hoc analysis, and for dashboards and reports that are essential for decision making. In this post, we describe a new set of BI tools that continue this trend.
- Compute Goes Brrr: Revisiting Sutton’s Bitter Lesson for AI - Nov 19, 2020.
"It's just about having more compute." Wait, is that really all there is to AI? As Richard Sutton's 'bitter lesson' sinks in for more AI researchers, a debate has stirred that considers a potentially more subtle relationship between advancements in AI based on ever-more-clever algorithms and massively scaled computational power.
- AI Is More Than a Model: Four Steps to Complete Workflow Success - Nov 17, 2020.
The key element for success in practical AI implementation is uncovering any issues early on and knowing what aspects of the workflow to focus time and resources on for the best results—and it’s not always the most obvious steps.
- How to use AI & analytics now to prepare for resiliency in 2021 - Nov 11, 2020.
Emerge with Resiliency 2020 is a no-cost virtual event presented by the IBM Planning Analytics and Cognos Community taking place on Nov 18. This one-day event includes 8 expert sessions, during which you’ll learn how IBM solutions can help enhance business continuity, reduce risk from emerging threats, and help you prepare for and manage disruption.
- Overcoming the Racial Bias in AI - Oct 30, 2020.
The results of any AI developed today is entirely dependent on the data on which it trains. If the data is distributed--intentionally or not--with a bias toward any category of data over another, then the AI will display that bias. What is a better way forward to handle this possibility toward bias when the datasets involve human beings?
- Explaining the Explainable AI: A 2-Stage Approach - Oct 29, 2020.
Understanding how to build AI models is one thing. Understanding why AI models provide the results they provide is another. Even more so, explaining any type of understanding of AI models to humans is yet another challenging layer that must be addressed if we are to develop a complete approach to Explainable AI.
- An Introduction to AI, updated - Oct 28, 2020.
We provide an introduction to key concepts and methods in AI, covering Machine Learning and Deep Learning, with an updated extensive list that includes Narrow AI, Super Intelligence, and Classic Artificial Intelligence, as well as recent ideas of NeuroSymbolic AI, Neuroevolution, and Federated Learning.
- Can AI Learn Human Values? - Oct 27, 2020.
OpenAI believes that the path to safe AI requires social sciences.
- The Ethics of AI - Oct 21, 2020.
Marketing scientist Kevin Gray asks Dr. Anna Farzindar of the University of Southern California about a very important subject - the ethics of AI.
- Cartoon: Cloud Dating - Oct 17, 2020.
New KDnuggets cartoon looks at how AI can transform love and romance.
- Getting Started in AI Research - Oct 5, 2020.
A guide on how to contribute to confirming the reproducibility of some of the most recent papers and join open-search research.
- Top KDnuggets tweets, Sep 23-29: An Introduction to #AI – updated for 2020; Master using Pandas for time series analysis - Sep 30, 2020.
An Introduction to #AI - updated for 2020; Free From MIT: Intro to Computer Science and Programming in Python; The Most Complete Guide to #PyTorch for Data Scientists; (Good) Data Cleaning is just reusable Data Transformations
- AI in Healthcare: A review of innovative startups - Sep 30, 2020.
The AI innovation in healthcare has been overwhelming with the Global Healthcare AI Market accounting for $0.95 billion in 2017, and is expected to reach $19.25 billion by 2026. What drives this vibrant growth?
- How AI is Driving Innovation in Astronomy - Sep 29, 2020.
In this blog, we look at a disruptive AI program - Morpheus - developed by Researchers at UC Santa Cruz that can analyze astronomical image data and classify galaxies and stars with surgical precision. If you're reading this with "starry" eyes, we bet we've got you hooked.
- Artificial Intelligence for Precision Medicine and Better Healthcare - Sep 23, 2020.
In this article, we will focus on various machine learning, deep learning models, and applications of AI which can pave the way for a new data-centric era of discovery in healthcare.
- Can Neural Networks Show Imagination? DeepMind Thinks They Can - Sep 16, 2020.
DeepMind has done some of the relevant work in the area of simulating imagination in deep learning systems.
- Online Certificates/Courses in AI, Data Science, Machine Learning from Top Universities - Sep 16, 2020.
We present the online courses and certificates in AI, Data Science, Machine Learning, and related topics from the top 20 universities in the world.
- Big Data and AI Toronto Goes Virtual - Sep 14, 2020.
The Big Data and AI Toronto Conference and Expo returns on September 29-30, 2020 with a brand new format and will be held exclusively online. KDnuggets readers get a 25% discount on all-access passes with promo code BDTORONTO-25. Register now.
- AI Papers to Read in 2020 - Sep 10, 2020.
Reading suggestions to keep you up-to-date with the latest and classic breakthroughs in AI and Data Science.
- 8 AI/Machine Learning Projects To Make Your Portfolio Stand Out - Sep 9, 2020.
If you are just starting down a path toward a career in Data Science, or you are already a seasoned practitioner, then keeping active to advance your experience through side projects is invaluable to take you to the next professional level. These eight interesting project ideas with source code and reference articles will jump start you to thinking outside of the box.
- Showcasing the Benefits of Software Optimizations for AI Workloads on Intel® Xeon® Scalable Platforms - Sep 1, 2020.
The focus of this blog is to bring to light that continued software optimizations can boost performance not only for the latest platforms, but also for the current install base from prior generations. This means customers can continue to extract value from their current platform investments.
- A Curious Theory About the Consciousness Debate in AI - Aug 31, 2020.
Dr. Michio Kaku has formulated a very interesting theory of consciousness that applies to AI systems.
- Beyond the Turing Test - Aug 28, 2020.
With more advancements in AI, it might be time to replace the age-old Turing Test with something better to determine if a machine is thinking. Specifically, a more modern approach might include standard questions designed to probe various facets of intelligence, and comparing the computer to a spectrum of human respondents of different ages, sexes, backgrounds, and abilities.
- DeepMind’s Three Pillars for Building Robust Machine Learning Systems - Aug 24, 2020.
Specification Testing, Robust Training and Formal Verification are three elements that the AI powerhouse believe hold the essence of robust machine learning models.
- Rapid Python Model Deployment with FICO Xpress Insight - Aug 20, 2020.
The biggest hurdle in the use of data to create business value, is indeed the ability to operationalize analytics throughout the organization. Xpress Insight is geared to reduce the burden on IT and address their critical requirements while empowering business users to take ownership of decisions and change management.
- Top Google AI, Machine Learning Tools for Everyone - Aug 18, 2020.
Google is much more than a search company. Learn about all the tools they are developing to help turn your ideas into reality through Google AI.
- Are Computer Vision Models Vulnerable to Weight Poisoning Attacks? - Aug 17, 2020.
A recent paper has explored the possibility of influencing the predictions of a freshly trained Natural Language Processing (NLP) model by tweaking the weights re-used in its training. his result is especially interesting if it proves to transfer also to the context of Computer Vision (CV) since there, the usage of pre-trained weights is widespread.
- KDnuggets™ News 20:n30, Aug 5: What Employers are Expecting of Data Scientist Role; I have a joke about… - Aug 5, 2020.
Know What Employers are Expecting for a Data Scientist Role in 2020; I have a joke about …; First Steps of a Data Science Project; Why You Should Get Google's New Machine Learning Certificate; Awesome Machine Learning and AI Courses
- Awesome Machine Learning and AI Courses - Jul 30, 2020.
Check out this list of awesome, free machine learning and artificial intelligence courses with video lectures.
- The Bitter Lesson of Machine Learning - Jul 15, 2020.
Since that renowned conference at Dartmouth College in 1956, AI research has experienced many crests and troughs of progress through the years. From the many lessons learned during this time, some have needed to be re-learned -- repeatedly -- and the most important of which has also been the most difficult to accept by many researchers.
- 5 Innovative AI Software Companies You Should Know - Jul 8, 2020.
While machine learning is impacting organizations around the world, some are driving forward the real-world applications of innovative AI. Check out these interesting companies to watch for exciting new progress this year.
- Scope and Impact of AI in Agriculture - Jul 6, 2020.
The major advantage of focusing on AI-based methods is that they tackle each of the challenges faced by farmers from seed sowing to harvesting of crops separately and rather than generalising, provide customised solutions to a specific problem.
- Tools to Spot Deepfakes and AI-Generated Text - Jun 23, 2020.
The technologies that generate deepfake content is at the forefront of manipulating humans. While the research developing these algorithms is fascinating and will lead to powerful tools that enhance the way people create and work, in the wrong hands, these same tools drive misinformation at a scale we can't yet imagine. Stopping these bad actors using awesome tools is in your hands.
- Bias in AI: A Primer - Jun 23, 2020.
Those interested in studying AI bias, but who lack a starting point, would do well to check out this introductory set of slides and the accompanying talk on the subject from Google researcher Margaret Mitchell.
- What is emotion AI and why should you care? - Jun 19, 2020.
What is emotion AI, why is it relevant, and what do you need to know about it?
- How to make AI/Machine Learning models resilient during COVID-19 crisis - Jun 11, 2020.
COVID-19-driven concept shift has created concern over the usage of AI/ML to continue to drive business value following cases of inaccurate outputs and misleading results from a variety of fields. Data Science teams must invest effort in post-model tracking and management as well as deploy an agility in the AI/ML process to curb problems related to concept shift.
- GPT-3, a giant step for Deep Learning and NLP? - Jun 9, 2020.
Recently, OpenAI announced a new successor to their language model, GPT-3, that is now the largest model trained so far with 175 billion parameters. Training a language model this large has its merits and limitations, so this article covers some of its most interesting and important aspects.
- Why Do AI Systems Need Human Intervention to Work Well? - Jun 5, 2020.
All is not well with artificial intelligence-based systems during the coronavirus pandemic. No, the virus does not impact AI – however, it does impact humans, without whom AI and ML systems cannot function properly. Surprised?
- Upcoming Webinars and Online Events in AI, Data Science, Machine Learning: June - Jun 4, 2020.
Here are some interesting upcoming webinar, online events and virtual conferences in in AI, Data Science, and Machine Learning.
- 5 Essential Papers on AI Training Data - Jun 4, 2020.
Data pre-processing is not only the largest time sink for most Data Scientists, but it is also the most crucial aspect of the work. Learn more about training data and data processing tasks from 5 leading academic papers.
- Privacy-preserving AI – Why do we need it? - May 29, 2020.
Various data privacy threats can result from the usual process of building and constructing data and AI-based systems. Avoiding these challenges can be supported by utilizing state-of-the-art technologies in the domain of privacy-preserving AI.
- Are Tera Operations Per Second (TOPS) Just hype? Or Dark AI Silicon in Disguise? - May 27, 2020.
This article explains why TOPS isn’t as accurate a gauge as many people think, and discusses other criteria that should be considered when evaluating a solution to a real application.
- Deepmind’s Gaming Streak: The Rise of AI Dominance - May 27, 2020.
There is still a long way to go before machine agents match overall human gaming prowess, but Deepmind’s gaming research focus has shown a clear progression of substantial progress.
- Machine Fairness: How to assess AI system’s fairness and mitigate any observed unfairness issues - May 26, 2020.
Microsoft is bringing the latest research in responsible AI to Azure (both Azure Machine Learning and their open source toolkits), to empower data scientists and developers to understand machine learning models, protect people and their data, and control the end-to-end machine learning process.
- 13 must-read papers from AI experts - May 20, 2020.
What research articles do top AI experts in the field recommend? Find out which ones and why, then be sure to add each to your reading to do list.
- AI Channels to Follow - May 15, 2020.
AI is certainly playing an important role in our global fight against the novel coronavirus. These YouTube channels are recommended to keep you covered with the latest advancements in the field and how it is impacting our world.
- AI and Machine Learning for Healthcare - May 14, 2020.
Traditional business and technology sectors are not the only fields being impacted by AI. Healthcare is a field that is thought to be highly suitable for the applications of AI tools and techniques.
- DeepMind’s Suggestions for Learning #AtHomeWithAI - May 13, 2020.
DeepMind has been sharing resources for learning AI at home on their Twitter account. Check out a few of these suggestions here, and keep your eye on the #AtHomeWithAI hashtag for more.
- Demystifying the AI Infrastructure Stack - May 1, 2020.
AI tools and services are expanding at a rapid clip, and keeping a handle on this evolving ecosystem is crucial for the success of your AI projects. This framework will help you build your technical stack to deploy AI projects faster and at scale.
- Introducing Brain Simulator II: A New Platform for AGI Experimentation - Apr 29, 2020.
A growing consensus of researchers contend that new algorithms are needed to transform narrow AI to AGI. Brain Simulator II is free software for new algorithm development targeted at AGI that you can experiment with and participate in its development.
- How AI Can Help Manage Infectious Diseases - Apr 28, 2020.
With the capability to analyze huge amounts of data, including medical information, human behavior patterns, and environmental conditions, big data tools can be invaluable in dealing with deadly outbreaks.
- 3 Reasons Why We Are Far From Achieving Artificial General Intelligence - Apr 23, 2020.
How far we are from achieving Artificial General Intelligence? We answer this through the study of three limitations of current machine learning.
- Fighting Coronavirus With AI: Improving Testing with Deep Learning and Computer Vision - Apr 22, 2020.
This post will cover how testing is done for the coronavirus, why it's important in battling the pandemic, and how deep learning tools for medical imaging can help us improve the quality of COVID-19 testing.
- KDnuggets™ News 20:n16, Apr 22: Scaling Pandas with Dask for Big Data; Dive Into Deep Learning: The Free eBook - Apr 22, 2020.
4 Steps to ensure your AI/Machine Learning system survives COVID-19; State of the Machine Learning and AI Industry; A Key Missing Part of the Machine Learning Stack; 5 Papers on CNNs Every Data Scientist Should Read
- 4 Steps to ensure your AI/Machine Learning system survives COVID-19 - Apr 17, 2020.
Many AI models rely on historical data to make predictions on future behavior. So, what happens when consumer behavior across the planet makes a 180 degree flip? Companies are quickly seeing less value from some AI systems as training data is no longer relevant when user behaviors and preferences change so drastically. Those who are flexible can make it through this crisis in data, and these four techniques will help you stay in front of the competition.
- State of the Machine Learning and AI Industry - Apr 16, 2020.
Enterprises are struggling to launch machine learning models that encapsulate the optimization of business processes. These are now the essential components of data-driven applications and AI services that can improve legacy rule-based business processes, increase productivity, and deliver results. In the current state of the industry, many companies are turning to off-the-shelf platforms to increase expectations for success in applying machine learning.
- DeepMind Unveils Agent57, the First AI Agents that Outperforms Human Benchmarks in 57 Atari Games - Apr 13, 2020.
The new reinforcement learning agent innovates over previous architectures achieving one of the most important milestones in the AI space.
- Has AI Come Full Circle? A data science journey, or why I accepted a data science job - Apr 10, 2020.
Personal journeys in Data Science can vary greatly between individuals. Some are just getting starting and wading into this vast ocean of opportunity, and others have been involved during its decades-long evolution as a professional field. This review of a longer journey can provide a broader perspective of how you might fit into this interesting career.
- Successful Use Cases of Artificial Intelligence for Businesses - Apr 10, 2020.
AI is contributing to the businesses in a huge way. For specifics, check out these successful use cases of AI for business.
- 10 Must-read Machine Learning Articles (March 2020) - Apr 9, 2020.
This list will feature some of the recent work and discoveries happening in machine learning, as well as guides and resources for both beginner and intermediate data scientists.
- Cartoon: AI understanding of Coronavirus - Apr 1, 2020.
Here is a cartoon to distract you, showing a new level of understanding AI could reach.
- Want to Build an AI Model for Your Business? Read this - Mar 25, 2020.
The best approach for AI production is similar to what venture capitalists (VC’s) do when they evaluate and invest in startups.
- Top AI Resources – Directory for Remote Learning - Mar 24, 2020.
Whether you are just learning Data Science, a current professional, or just interested, it's crucial to keep the mind stimulated and stay current. With conferences, schools, and travel largely canceled because of #coronavirus, these remote resources will help you stay engaged.
- Unlocking the Potential of FAIR Data Using AI at Roche - Mar 9, 2020.
Learn from the head of the data science department in research and early development at Roche. Use the code KDNUGGETS for a 15% discount on your Predictive Analytics World ticket, 11-12 May in Munich.
- Resources for Women in AI, Data Science, and Machine Learning - Mar 8, 2020.
For the international women's day, we feature resources to help more women enter and succeed in AI, Big Data, Data Science, and Machine Learning fields.
- 20 AI, Data Science, Machine Learning Terms You Need to Know in 2020 (Part 2) - Mar 2, 2020.
We explain important AI, ML, Data Science terms you should know in 2020, including Double Descent, Ethics in AI, Explainability (Explainable AI), Full Stack Data Science, Geospatial, GPT-2, NLG (Natural Language Generation), PyTorch, Reinforcement Learning, and Transformer Architecture.
- Prepare for a Long Battle against Deepfakes - Feb 21, 2020.
While deepfakes threaten to destroy our perception of reality, the tech giants are throwing down the gauntlet and working to enhance the state of the art in combating doctored videos and images.
- How Kubeflow Can Add AI to Your Kubernetes Deployments - Feb 21, 2020.
As Kubernetes is capable of working with other solutions, it is possible to integrate it with a collection of tools that can almost fully automate your development pipeline. Some of those third-party tools even allow you to integrate AI into Kubernetes. One such tool you can integrate with Kubernetes is Kubeflow. Read more about it here.
- Hand labeling is the past. The future is #NoLabel AI - Feb 19, 2020.
Data labeling is so hot right now… but could this rapidly emerging market face disruption from a small team at Stanford and the Snorkel open source project, which enables highly efficient programmatic labeling that is 10 to 1,000x as efficient as hand labeling?
- KDnuggets™ News 20:n07, Feb 19: 20 AI, Data Science, Machine Learning Terms for 2020; Why Did I Reject a Data Scientist Job? - Feb 19, 2020.
This week on KDnuggets: 20 AI, Data Science, Machine Learning Terms You Need to Know in 2020; Why Did I Reject a Data Scientist Job?; Fourier Transformation for a Data Scientist; Math for Programmers; Deep Neural Networks; Practical Hyperparameter Optimization; and much more!
- 20 AI, Data Science, Machine Learning Terms You Need to Know in 2020 (Part 1) - Feb 18, 2020.
2020 is well underway, and we bring you 20 AI, data science, and machine learning terms we should all be familiar with as the year marches onward.
- Using AI to Identify Wildlife in Camera Trap Images from the Serengeti - Feb 17, 2020.
With recent developments in machine learning and computer vision, we acquired the tools to provide the biodiversity community with an ability to tap the potential of the knowledge generated automatically with systems triggered by a combination of heat and motion.
- Top KDnuggets tweets, Feb 05-11: #SciPy 1.0: fundamental algorithms for scientific computing in #Python; Why is Data Science so popular? - Feb 12, 2020.
Why is Data Science so Popular?; Visual Paper Summary: ALBERT (A Lite BERT); Uber Has Assembled One of the Most Impressive Open Source DL Stacks; Top #AI Influencers To Follow in 2020
- AI and Machine Learning In Our Every Day Life - Feb 7, 2020.
The curiosity and buzz around the most talked-about technology -- Artificial Intelligence -- have experts and technophiles busy decoding its exciting future applications. Of course, the use of AI and machine learning is already pervasive in our daily lives, as we review many of these popular features in this article.
- The Data Science Puzzle — 2020 Edition - Feb 7, 2020.
The data science puzzle is once again re-examined through the relationship between several key concepts of the landscape, incorporating updates and observations since last time. Check out the results here.
- The Future of Machine Learning Will Include a Lot Less Engineering - Feb 6, 2020.
Despite getting less attention, the systems-level design and engineering challenges in ML are still very important — creating something useful requires more than building good models, it requires building good systems.
- Intro to Machine Learning and AI based on high school knowledge - Feb 5, 2020.
Machine learning information is becoming pervasive in the media as well as a core skill in new, important job sectors. Getting started in the field can require learning complex concepts, and this article outlines an approach on how to begin learning about these exciting topics based on high school knowledge.
- Top 5 Data Science Trends for 2020 - Feb 4, 2020.
As Data Science continues to expand into the next decade, this article features five important trends in the field that are expected in 2020. Leverage these trends to help improve your business processes for maximizing growth.
- OpenAI is Adopting PyTorch… They Aren’t Alone - Jan 31, 2020.
OpenAI is moving to PyTorch for the bulk of their research work. This might be a high-profile adoption, but it is far from the only such example.
- A bird’s-eye view of modern AI from NeurIPS 2019 - Jan 28, 2020.
With the explosion of the field of AI/ML impacting so many applications and industries, there is great value coming out of recent progress. This review highlights many research areas covered at the NeurIPS 2019 conference recently held in Vancouver, Canada, and features many important areas of progress we expect to see in the coming year.
- NLP Year in Review — 2019 - Jan 23, 2020.
In this blog post, I want to highlight some of the most important stories related to machine learning and NLP that I came across in 2019.
- Top 5 AI trends for 2020 - Jan 21, 2020.
We are all witnessing a staggering growth of AI technology with so many new benefits for people while also changing the way we live and work. As AI continues to grow, which applications will have a significant impact in 2020?
- Artificial Intelligence Books to Read in 2020 - Jan 21, 2020.
Here are some AI-related books that I’ve read and recommend for you to add to your 2020 reading list!
- We Created a Lazy AI - Jan 20, 2020.
This article is an overview of how to design and implement reinforcement learning for the real world.
- Top 10 Technology Trends for 2020 - Jan 16, 2020.
With integrations of multiple emerging technologies just in the past year, AI development continues at a fast pace. Following the blueprint of science and technology advancements in 2019, we predict 10 trends we expect to see in 2020 and beyond.
- Disentangling disentanglement: Ideas from NeurIPS 2019 - Jan 15, 2020.
This year’s NEURIPS-2019 Vancouver conference recently concluded and featured a dozen papers on disentanglement in deep learning. What is this idea and why is it so interesting in machine learning? This summary of these papers will give you initial insight in disentanglement as well as ideas on what you can explore next.
- 7 AI Use Cases Transforming Live Sports Production and Distribution - Jan 14, 2020.
Here are 7 powerful AI led use cases both for linear television and for OTT apps that are transforming the live sports production landscape.
- Deepfakes Security Risks - Jan 10, 2020.
Deepfakes have instilled panic in experts since they first emerged in 2017. Microsoft and Facebook have recently announced a contest to identify deepfakes more efficiently.
- 5 Ways AI Is Changing The Healthcare Industry - Jan 7, 2020.
The healthcare AI market is expected to reach 28 billion dollars by the year 2025. With such exponential growth, AI is undoubtedly likely to bring some drastic changes in the healthcare industry. Let’s look at five ways of how AI has changed the healthcare industry.
- Cartoon: Teaching Ethics to AI - Jan 4, 2020.
Ethics in AI has received significant attention recently, and the new KDnuggets cartoon examines the problem of teaching ethics to artificially intelligent entities.
- Towards a Quantitative Measure of Intelligence: Breaking Down One of the Most Important AI Papers of 2019, Part II - Dec 31, 2019.
AI scientist Francois Chollet proposes a better framework for measuring the intelligence of AI systems.
- Towards a Quantitative Measure of Intelligence: Breaking Down One of the Most Important AI Papers of 2019, Part I - Dec 30, 2019.
AI scientist Francois Chollet proposes a better framework for measuring the intelligence of AI systems.
- Google’s New Explainable AI Service - Dec 20, 2019.
Google has started offering a new service for “explainable AI” or XAI, as it is fashionably called. Presently offered tools are modest, but the intent is in the right direction.
- Xavier Amatriain’s Machine Learning and Artificial Intelligence 2019 Year-end Roundup - Dec 16, 2019.
It is an annual tradition for Xavier Amatriain to write a year-end retrospective of advances in AI/ML, and this year is no different. Gain an understanding of the important developments of the past year, as well as insights into what expect in 2020.
- What just happened in the world of AI? - Dec 12, 2019.
The speed at which AI made advancements and news during 2019 makes it imperative now to step back and place these events into order and perspective. It's important to separate the interest that any one advancement initially attracts, from its actual gravity and its consequential influence on the field. This review unfolds the parallel threads of these AI stories over this year and isolates their significance.
- AI, Analytics, Machine Learning, Data Science, Deep Learning Technology Main Developments in 2019 and Key Trends for 2020 - Dec 11, 2019.
We asked leading experts - what are the most important developments of 2019 and 2020 key trends in AI, Analytics, Machine Learning, Data Science, and Deep Learning? This blog focuses mainly on technology and deployment.
- AI, Analytics, Machine Learning, Data Science, Deep Learning Research Main Developments in 2019 and Key Trends for 2020 - Dec 9, 2019.
As we say goodbye to one year and look forward to another, KDnuggets has once again solicited opinions from numerous research & technology experts as to the most important developments of 2019 and their 2020 key trend predictions.
- Accuracy Fallacy: The Media’s Coverage of AI Is Bogus - Dec 6, 2019.
Such as the gross exaggerations Stanford researchers broadcasted about their infamous "AI gaydar" project, there exists a prevalent "accuracy fallacy" in relation to AI from the media. Find out more about how the press constantly misleads the public into believing that machine learning can reliably predict psychosis, heart attacks, sexuality, and much more.
- Artificial Friend or Virtual Foe - Dec 5, 2019.
Is AI making more good than harm?
- Top 7 Data Science Use Cases in Trust and Security - Dec 2, 2019.
What are trust and safety? What is the role of trust and security in the modern world? Read this overview of 7 data science application use cases in the realm of trust and security.
- Two Years In The Life of AI, Machine Learning, Deep Learning and Java - Nov 29, 2019.
Where does Java stand in the world of artificial intelligence, machine learning, and deep learning? Learn more about how to do these things in Java, and the libraries and frameworks to use.
- Open Source Projects by Google, Uber and Facebook for Data Science and AI - Nov 28, 2019.
Open source is becoming the standard for sharing and improving technology. Some of the largest organizations in the world namely: Google, Facebook and Uber are open sourcing their own technologies that they use in their workflow to the public.
- On the sensationalism of artificial intelligence news - Nov 15, 2019.
With artificial intelligence and machine learning now a mainstay of our daily awareness, news organizations have been seen to overstate the reality behind progress in the field. Learn more about recent examples of media hyperbole and explore why this may be happening.
- AI ROI: The Questions You Need To Be Asking - Nov 14, 2019.
During this free Metis Corporate Training webinar, Dec 5 @ 12pm ET, Kerstin Frailey, Senior Data Scientist and Head of Executive Corporate Training at Metis, will walk through what you need to ask before, during, and after the lifetime of a data science project to accurately assess its impact on the business.
- The Last Defense Against Another AI Winter - Nov 6, 2019.
My short answer is this: Yes, another AI Winter will be here if you don’t deploy more ML solutions. You and your Data Science teams are the last line of defense against the AI Winter. You need to solve five key challenges to keep the momentum up.
- KDnuggets™ News 19:n42, Nov 6: 5 Statistical Traps Data Scientists Should Avoid; 10 Free Must-Read Books on AI - Nov 6, 2019.
Learn about statistical fallacies Data Scientists should avoid; New and quite amazing Deep Learning capabilities FB has been quietly open-sourcing; Top Machine Learning tools for Developers; How to build a Neural Network from scratch and more.