Category Archives: Artificial Intelligence

Artificial Intelligence

As we wrap up the year, Ill start by pointing out something obvious to anyone who reads my column: Ive rarely mentioned the Covid-19 pandemic. While it has had a major impact on many areas of society, I dont feel that it has changed the artificial intelligence (AI) and machine learning (ML) markets in a significant way. At most, it has accelerated the adoption of the technology, but it hasnt done much. While I hope everyone remains as safe as possible, it is not something in my coverage area. My best wishes to all readers remain.

At the end of 2019, my similar column mentioned retail uses of vision and chatbots being more integrated into other applications during 2020. That happened and chatbots have now become a must have in most customer interaction interfaces. That has meant a more minimal coverage this year. Retail use of AI vision continues to expand, but in the opposite way of the acceleration mentioned in the first paragraph. The pandemic caused slowdown in retail means spending has slowed while survival is at stake. I expect to see that pick up again in the second half of 2021, as the vaccines become more widespread and consumer confidence improves.

What was exciting about 2020 was the clear evidence of AI tools moving out of the standard worlds of core enterprise data analysis, marketing, retail vision and facial recognition. Two areas discussed in multiple columns were in infrastructure.

The first of those areas is in the cable industry. The large ISPs are focused on better analyzing and optimizing their networks. Smaller companies have come along and are helping the large firms by beginning to use AI at the edge, enhancing modems and routers to better analyze where problems are originating in households. That will improve the experience both for households and the internet providers.

The second was a bundle of segments around facilities. AI is being used to enhance everything from planning through construction and maintenance. One of the more intriguing aspects was the use vision and ML to help businesses and government analyze physical structures in the real world. In the construction arena, AI vision and analysis are helping to better manage and schedule projects.

Discussions with a few vendors shows that artificial intelligence is also working its way into different areas of the sales process. This is a slower change, only adding a bit more accuracy to sales systems in enterprise sales. That will continue, but the real advances I see are coming from the more commoditized markets. Earlier this month, I described the complexity of the commodity channels and sales policies. In this area, I see more visible and rapid adoption of AI to better optimize the channels, while enterprise sales will see a more steady, gradual adoption that is still important.

When looking to 2020 and the future, I still see governments moving slowly. Thats not a surprise. The USA, plenty of other nations, and the EU, have been putting out policy statements, but thats really all there is. A few statements by people in Congress have shown an increasing interest in the subject, and the Bipartisan Policy Center is looking at it, but still having an Inside the Beltway view of the issue.

Departments are beginning to look at the issue. As healthcare has been an early adopter of AI, especially in radiology, the FDA has begun to look at the issue. A number companies mentioned that the FDA is looking at how to adapt policies to manage changing algorithms, as usual the organization itself isnt forthcoming. Talking to anyone in the FDA involved in defining the process was not possible, all that was sent to me was vague statements. Seeing how that evolves in the coming year will be interesting.

On the other hand, NGOs are also busy pushing out opinions, policy statements and books. In 2020, Ive discussed information from the Brookings Institution and the World Economic Forum (WEF). Brookings has some interesting things going on and Ill continue to watch the evolution of their AI understanding and views. The WEF, being a business group, has almost completely avoided mentioning governments at all. Theyve put out general statements about business ethics with AI, but the regulatory environment will be changing. I dont expect to see anything significant next year, but I would hope theres momentum building for action in 2022.

I have constantly returned to the refrain that AI is not a panacea, its a tool. One thing preventing wider adoption of the tool is that development software is moving more slowly than I hoped. There have been some user interface changes, with the basics of a graphical user interface (GUI) being layered on some aspects of the development cycle, but theres still a long way to go.

There needs to be a change similar to that between Third Generation programming languages to Fourth Generation languages, where coding was minimized, and graphical tools made it easier for less technical personnel to build applications supporting their business needs.

One trend I see helping that is that the importance of data privacy has filtered down to the developers. Data cleansing has usually been, sadly, an afterthought. As it becomes more important, and ML uses larger bodies of data, the need to quickly manage that data will drive UI changes. That will hopefully bubble up from managing privacy, to analyzing features for selection, to higher level management of the development process.

Frameworks, such as TensorFlow, as still the main tool for developing ML engines. That requires both more time and more money, as they are complex and require more knowledge and a higher price tag for programmers. While schools are working to meet the demand, theres also a need to increase the supply by providing more abstract tools that allow more people to leverage the power and promise of AI/ML.

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The Obligatory Artificial Intelligence Year End Article, 2020 Edition - Forbes

While 84 percent of global business organizations believe that AI can give them a competitive advantage and help recover faster from COVID-19, fewer than 23 percent of these firms have implemented this type of technology within their organization to date.

NEW YORK (PRWEB) December 31, 2020

Mediaplanet today announces the launch of this Decembers edition of Business Artificial Intelligence. This campaign spotlights how artificial intelligence (AI) is making it possible for businesses to address specific challenges during the ongoing pandemic.

Over the past nine months, the COVID-19 pandemic has brought multiple changes to our lives, including our working lives. While 84 percent of global business organizations believe that AI can give them a competitive advantage and help recover faster from COVID-19, fewer than 23 percent of these firms have implemented this type of technology within their organization to date.

To address this discrepancy, this campaign serves as an educational guidebook for the modern IT and business decision maker. Bringing together leading associations, thought leaders, and influencers from Americas core economic sectors who look to improve readers understanding of what AI is best suited to accomplish and how to deploy it for the most effective post-COVID-19 recovery of their organization. AI-driven technologies are empowering organizations to better navigate these unprecedented times and more effectively increase efficiencies, augment human labor, improve customer experiences, grow their bottom line, and provide firms with a clear advantage over competitors.

The print component of Business Artificial Intelligence is distributed within todays edition of USA TODAY, with a circulation of approximately 200,000 copies and an estimated readership of 600,000. The digital component is distributed nationally, through a vast social media strategy, and across a network of top news sites and partner outlets. To explore the digital version of the campaign, visit: https://www.futureofbusinessandtech.com/campaign/business-ai/

This campaign was made possible with the support of NICE, Steve Wozniak, Sprinklr, Kevin O'Leary, SOCAP International, Customer Experience Professionals Association, North American Association of Sales Engineers, Conversica, Khoros, GEP, Blue Prism, American Society of Mechanical Egineers, Kirk Borne, Institute of Business Forecasting, Association of Supply Chain Management, Council of Supply Chain Management Professionals, Reverse Logistics Institute, Michelle Meyer, Jim Tompkins, IEEE Computation Intelligence Society, Institute for Digital Transformation, Ai4All, Marketing AI Institute, AA-ISP, National Retail Federation, Steve Escaravage, Booz Allen Hamilton and GEP.

About Mediaplanet Mediaplanet specializes in the creation of content marketing campaigns covering a variety of industries. We tell meaningful stories that educate our audience and position our clients as solution providers. Our unique ability to pair the right leaders with the right readers, through the right platforms, has made Mediaplanet a global content marketing powerhouse. Our award-winning stories have won the hearts of countless readers while serving as a valuable platform for brands and their missions. Just call us storytellers with a purpose. Please visit http://www.mediaplanet.com for more on who we are and what we do.

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Mediaplanet Outlines the Potential of Artificial Intelligence in Economic Recovery in New Business AI Campaign - PR Web

Artificial Intelligence (AI) is influencing the future of virtually every industry and each person on the planet. Artificial intelligence has been set up as the primary driver of growing technologies, for example, robotics, big data, and the Internet of Things (IoT). Moving into 2021, Artificial Intelligence will keep on going about as a principle technological pioneer for years to come.

Artificial intelligence is a highlight of the coming new normal in our entire lives. Going ahead, AI will be the intelligent core of robotic, automated, and contactless procedures that will shield us all from future outbreaks.

As indicated by the first published World Intellectual Property Organization WIPO report monitoring the advancement of technologies through the analysis of information on innovation activities, we can see drifts in patenting of Artificial Intelligence (AI) innovations, the top players in AI from industry and academia, and the geological dispersion of AI-related patent protection and scientific publications. The first of a series of WIPO reports on AI and patent analysis was published in 2019 and remains significant in issues of AI patterns.

In 2021, the grittiest of organizations will push AI to new boondocks, for example, holographic meetings for telecommunication and on-demand, personalised manufacturing. They will gamify vital planning, incorporate simulations in the meeting room and move into intelligent edge experiences.

Combined with this, fortunate laggards will utilize no-code automated machine learning to execute five, 50, or 500 AI use cases quicker, leaving behind their rivals with proficient, entrenched data science teams that take a customary, code-first way to deal with machine learning.

According to Rohan Amin, the Chief Information Officer at Chase, In 2021, we will see more refined uses of machine learning and artificial intelligence across industries, including financial services. There will be more noteworthy incorporation of AI/ML models and abilities into numerous business operations and processes to drive improved insights and better serve clients.

Further, Authenticated AI is very crucial. In 2021, companies will execute facial recognition for solid authentication in a developing range of internal and customer-facing applications. By a similar token, business will progressively neglect to utilize the innovation to surmise personality, gender, race, and other characteristics that may be sensitive from a bias, privacy, and surveillance viewpoint. To the degree that organizations consolidate facial recognition in picture/video auto-tagging, query-by-image, and other such applications, it might be after broad review by legal counsel. The administrative affectability of this innovation and the legitimate dangers will just develop for the foreseeable future.

As per Forresters forecast, the year 2021 will feature the great, the terrible, and the ugly of artificial data, which comes in two structures: Synthetic information that permits clients to make data sets for training AI, and fake information that does the inverse; it annoys training data to purposely lose AI.

Organizations are confronting increasing pressure from consumer interest groups and controllers to give a data lineage for AI. This incorporates data review trails to guarantee consistency and moral utilization of AI. In 2021, Blockchain and AI will begin uniting all the more genuinely to foster data provenance, integrity, and usage.

According to Flavio Bonomi, the Board Advisor to Lynx Software Technologies, 2021 is where AI will get embedded into existing devices and make certain operations quicker and more precise as standard. Sensors would now be able to recognize any of the five senses (indeed, including smell) and we will see AI progressively applied to those. Examples incorporate the capacity to identify vibrations or unordinary noises in a plant that ensures maintenance is performed on hardware before malfunctioning. Not as attractive or as clear as a self-driving vehicle, yet pragmatic and with a measurable ROI.

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Artificial Intelligence in 2021: Endless Opportunities and Growth - Analytics Insight

What better time than now to unveil what to look out for in the world of AI and technology in 2021.

By Prithwis De

The year 2020 will be marked as an unprecedented year in history due to the adverse impact of coronavirus worldwide. This pandemic has started bringing extraordinary changes in some key areas. The trends of faster drug development, effective remote care, efficient supply chain, etc, will continue into 2021. Drone technology is already playing a vital role in delivering food and other essentials alongside relief activities.

With Covid-19 came a new concept of the Internet of Behaviour within organisations to track human behaviour in the work environment and trace any slack in maintaining guidelines. Now on, organisations are set to capture and combine behaviour-related data from different sources and use it. We can assertively say it will affect the way organisations interact with people, going forward. Students are experiencing distance learning, taking examinations under remotely-monitored and proctored surveillance systems through identity verification and authentication in real time.

All these will have a high impact on technology, which will shape our outlook in the future. Businesses around the globe are taking the giant leap to become tech-savvy with quantum computing, artificial intelligence (AI), cybersecurity, etc. AI and cloud computing are alluring us all towards an environment of efficiency, security, optimisation and confidence. What better time than now to unveil what to look out for in the world of AI and technology in 2021.

What 2020 has paved the way for is quantum computing. Now, be prepared to adapt to a hybrid computing approach (conventional cum quantum computing) to problem-solving. This paradigm shift in computing will result in the emergence of implausible ways to solve existing business problems and ideate new opportunities. Its effects will be visible on our ability to perform better in diverse areasfinancial forecasting, weather predictions, drug and vaccine development, blood-protein analysis, supply chain planning and optimisation, etc. Quantum Computing as a Service (QCaaS) will be a natural choice for organisations to plug into the experiments as we advance. Forward-thinking businesses are excited to take the quantum leap, but the transition is still in a nascent stage. This new year will be a crucial stepping stone towards the future of things to change in the following years.

Cloud providers such as Amazon (AWS), Microsoft (Azure) and Google will continue to hog the limelight as the AI tool providers for most companies leaning towards real-time experiments in their business processes in the months to follow. Efficiency, security and customisation are the advantages for which serverless and hybrid cloud computing are gaining firm ground with big enterprises. It will continue to do so in 2021.

Going forward, the aim is to make the black box of AI transparent with explainable AI. The lack of clarity hampers our ability to trust AI yet. Automated machine learning (AutoML), another crucial area, is likely to be very popular in the near future. One more trend that caught on like wildfire in 2020 is Machine Learning Operations (MLOps). It provides organisations visibility of their models and has become an efficient tool to steer clear of duplicated efforts in AI. Most of the companies have been graduating from AI experimentations and pilot projects to implementation. This endeavour is bound to grow further and enable AI experts to have more control over their work from end-to-end now onwards.

Cybersecurity will gain prime importance in 2021 and beyond as there is no doubt that hacking and cybercrime prevention are priorities for all businesses with sensitive data becoming easily accessible with advanced phishing tools. Advanced prediction algorithms, along with AI, will play a decisive role in the future to prevent such breaches in data security.

AI and the Internet of Things along with edge computing, which is data processing nearer the source closer to the device at the edge of the network, will usher in a new era for actionable insights from the vast amount of data. The in-memory-accelerated-real-time AI will be needed, particularly when 5G has started creating new opportunities for disruption.

In 2020, there was a dip in overall funding as the pandemic had badly impacted the investment sector due to a reduction in activity. Some of the technology start-ups are still unable to cope up with the challenges created due to Covid-19 and the consequent worsening economic conditions. According to NASSCOM, around 40% of Indian start-ups were forced to stop their operations. In 2021, mergers and acquisitions of start-ups are expected. The larger companies are likely to target smaller companies, specialised mainly in niche and innovative areas such as drug development, cybersecurity, AI chips, cloud computing, MLOps, etc.

The businesses in 2021 and beyond will develop into efficient workplaces for everybody who believes in the power of technology. It is important to bear in mind that all trends are not necessarily independent of each other, but rather form the support base of the other as well as work in tandem with human intervention. So, are the hybrid trends and solutions here to stay for the next few years for the smooth running of various organisations? Only time will tell. But the need for AI and newer technology adoption and modernisation increases manifold.

The author is an analytics and AI professional, based in London, working in a big IT company. Views are personal

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Tech trends in 2021: How artificial intelligence and technology will reshape businesses - The Financial Express

Artificial intelligence (AI) has captivated the imagination of science-fiction movie audiences for many years and has been used in the upstream oil and gas industry for more than a decade (Mohaghegh 2005, 2011). But few industries evolve more quickly than those from Silicon Valley, and it accordingly follows that the technology has grown and changed considerably since this discussion began. The oil and gas industry, therefore, is at a point where it would be prudent to take stock of what has been achieved with AI in the sector, to provide a sober assessment of what has delivered value and what has not among the myriad implementations made so far, and to figure out how best to leverage this technology in the future in light of these learnings.

When one looks at the long arc of AI in the oil and gas industry, a few important truths emerge. First among these is the fact that not all AI is the same. There is a spectrum of technological sophistication. Hollywood and the media have always been fascinated by the idea of artificial superintelligence and general intelligence systems capable of mimicking the actions and behaviors of real people. Those kinds of systems would have the ability to learn, perceive, understand, and function in human-like ways (Joshi 2019). As alluring as these types of AI are, however, they bear little resemblance to what actually has been delivered to the upstream industry. Instead, we mostly have seen much less ambitious narrow AI applications that very capably handle a specific task, such as quickly digesting thousands of pages of historical reports (Kimbleton and Matson 2018), detecting potential failures in progressive cavity pumps (Jacobs 2018), predicting oil and gas exports (Windarto et al. 2017), offering improvements for reservoir models (Mohaghegh 2011), or estimating oil-recovery factors (Mahmoud et al. 2019).

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Artificial Intelligence in the E&P Industry: What Have We Learned So Far and Where to Next? - Journal of Petroleum Technology

Frommysterious monolithsto invasivemurder hornets, 2020 hasbeen a weird year, with even weirder headlines.

So weird, in fact, that when Colorado research scientist Janelle Shane fed a batch of actual 2020 headlines to a language-mimicking artificialintelligence called GPT-3, it generated some truly bizarre news of its own, including:"Massive Radioactive Sinkhole Continues to Grow in Russia" and"When Killer Orchids Attack: How the Deadly Corpse Orchid Is Turning Up in U.S. Backyards."

These AI-generated headlines soundexactly like the kind of quirky stories we love to cover on our program. So we asked Shaneto feed the AI some real 2020 headlines from As It Happens, and see what it would come up with.

The computer-generated headlines were so perfectly As It Happens-esque that even our own senior producer and assistant director couldn't always tell the difference.Watch them try it:

"I think we're seeing this kind of convergence between the world is very weird, and also AI has now seen enough weird headlines that it can, to some extent, figure out the right amount of weird to be," Shane said.

Want to try it yourself? Take our quiz below and see if you can spot the difference between real As It Happens headlines, and fake onesgenerated by an artificial intelligence. (If you're having trouble accessing the quiz below, try clicking here.)

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As It Happens vs. artificial intelligence: Can you tell which 2020 headlines are real? - CBC.ca

With a new generation of consoles at the door, the video game industry shows that it continues to work with the objective of offering its users better graphics and advanced technologies related to image and sound, but above all, to a factor that has had a constant evolution and that is key in the development of games from the beginning: Artificial Intelligence (AI).

We can understand artificial intelligence as the technology that, through so-called machine learning, allows a machine, system or software, to learn to analyze certain information from the environment in order to obtain a more human behavior. And although a few years ago this might seem like an aphorism taken from one of Asimovs works, it is a reality that has ended up reaching us as humans and that no longer belongs to the field of science fiction and speculation.

Within the world of video games, we could summarize and define artificial intelligence as the techniques used by developers to design the behavior of famous NPCs (Non Playable Characters). However, this is a definition that has become increasingly concise in the face of a technology that has been growing along with the video game industry itself, and that now not only focuses on determining the behavior of adversaries, but which is capable of designing increasingly demanding maps, levels and challenges for players. In some online casino list, they offer some games equipped with AI technology.

The origin of Artificial Intelligence in video games occurs before the industry itself became an essential part of popular culture worldwide. One of the best known precedents for the use of this technology in a game dates back to the 1950s, with computer chess titles that were developed based on the MiniMax algorithm. This software had the ability to analyze the position of the pieces on the board to choose the best possible move. Starting in the seventies, with video games revolutionizing the market and the entertainment experiences of users, Artificial Intelligence began to play a key role in the conception and development of the titles of major brands.

In 1972 Pong, your opponent was already able to move based on the movement of the ball you hit to return the impact, while Space Invaders gave clear signs of how the enemies evolved and were increasingly intelligent, challenging the players who they spent hours in the arcade trying to pass each of the levels.

For its part, in the eighties Pac-Man took another step, since it was the first video game that featured a route search system for enemies, who were able to more easily decipher the path that the player took under certain circumstances. In the same years, Donkey Kong boasted how much Artificial Intelligence had advanced, with a level of difficulty that pushed gamers of the time to the limit of their abilities. However, Artificial Intelligence was still precarious enough to realize that the machine was not capable of learning from its mistakes, nor of adapting to the behavior of the player, so the latter had to decipher certain patterns in order to get ahead of the most demanding challenges.

A big jump Artificial Intelligence in video games continued to evolve alongside products that increasingly had a more avid consumer base, and therefore, more demanding. It was thus that new possibilities began to be explored and in 1987 the Golden Ax video game innovated by allowing enemies to run after the player with the intention of attacking him from behind, something surprising if we take into account that at the time the adversaries did not stand out for their mobility.

Little by little, the big developers began to explore more complex terrain, and by 2011, the algorithms of Artificial Intelligence generated simple but unique missions by randomly configuring places, enemies and objectives in the ARPG, The Elder Scrolls V: Skyrim, thus taking a huge workload off the title designers.

Designing video games, the future of AI The role of Artificial Intelligence in the world of video games is increasingly decisive, and has gone from providing a higher level of realism to them, to designing them completely from scratch.

What is the most challenging Artificial Intelligence you have faced in all these years of evolution in video games?

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Analytics Insight is an influential platform dedicated to insights, trends, and opinions from the world of data-driven technologies. It monitors developments, recognition, and achievements made by Artificial Intelligence, Big Data and Analytics companies across the globe.

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The Evolution of Artificial Intelligence in Video Games - Analytics Insight

(For the Holiday Season, from Christmas through New Years Day. well post 2020s most viewed articles as ranked by Google Analytics.)

The research study of Spanish clinical neuropsychologist Gabriel G. De la Torre, Does artificial intelligence dream of non-terrestrial techno-signatures?, suggests that one of the potential applications of artificial intelligence is not only to assist in big data analysis but to help to discern possible artificiality or oddities in patterns of either radio signals, megastructures or techno-signatures in general.

Our form of life and intelligence, observed Silvano P. Colombano at NASAs Ames Research Center who was not involved in the study, may just be a tiny first step in a continuing evolution that may well produce forms of intelligence that are far superior to ours and no longer based on carbon machinery.

We Have Absolutely No Idea Whats Out There

The result of De la Torres intriguing visual experiment calls into question the application of artificial intelligence to the search for extra-terrestrial intelligence (SETI) where advanced and ancient technological civilizations may exist but be beyond our comprehension or ability to detect.

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Artificial Intelligence of the Future Could Reveal the Incomprehensible (2020 Most Viewed) - The Daily Galaxy --Great Discoveries Channel

The quick advancement of artificial intelligence can possibly revamp how the government provides an expansive range of core services to citizens in a significant manner. When implemented effectively, these innovations can assist the government with delivering decisions quicker, utilizing better information, at a far lower cost in essential areas going from granting disability advantages to granting patents to arbitrating migration applications and healthcare insurance benefits.

With quick digital technological change, it is inescapable for the government to advance its customary techniques to accomplish better citizen engagement, responsibility, and interoperability; and this should be possible by adapting to complex changing environment and getting tough with the utilization of intelligent technologies that can go about as the facilitators of development, competitiveness, sustainability, and liveability.

Artificial intelligence has a colossal potential in various government areas, for example, transportation, data security and management, education, healthcare, physical infrastructure, and so forth; and it is imperative for the government to perceive for implementing the same to improve the quality of life for the residents and efficiency of governance.

The Indian government has said that it will use artificial intelligence tools to set up better guidelines and ensure citizens privacy and ownership of data. The Minister of Commerce and Aviation said that the nation is moving more information than the United States and China put together. The main six organizations on the planet are utilizing this data with value addition and monetisation.

Further, India is fortifying its overall set of laws and administrative system to manage this universe of digital information.

Research on AI in the government sector is as yet in its incipient stage and just covers the normal effects of AI, which is speculative in nature and, there is a monstrous scope for empirical research on the AI applications alongside its difficulties as accepted by the partners working in the government area.

Numerous analysts and professionals have only referenced the technological parts of AI applications which sounds ambiguous without a robust public administration model that depicts the implications for governance of the administrative state. Corresponding to this contention, there is as yet a growing need for understanding the reach and impact of AI-based applications and related challenges in a holistic manner.

Automated decision support utilizes AI to apply hundreds or even a large number of discrete regulatory, technical, and business rules that are pertinent to an exact circumstance and place them at the fingertips of the knowledge worker. Complex issues that may have required the intercession of a CPA, engineer, or different experts can be envisioned and settled in advance. The organization can update business logic parameters to new regulatory interpretations or legislation without the requirement for extensive retraining.

As per the Policy Commissions National Strategy for AI, AI innovation provides safety through smart command centres with refined surveillance frameworks that keep checks on peoples movement, potential wrongdoing episodes, and general security of the inhabitants.

Social media intelligence platforms give help to public security by assembling data from social media and anticipate potential exercises that could disrupt public peace.

Artificial intelligence has a significant potential in climate sustainability-related issues as it has the abilities in the area of machine translation, natural language processing, data analytics and pattern recognition, or in computer vision and the latest advances being utilized is the modern machine learning and deep learning. The potential territories covered under the climate where AI can be applied range from applications in energy and utilities, agribusiness, to environmental protection.

Rigid business rules oversee what data sets can be accessed, the security of sensitive data, and how results are shared. Artificial intelligence can quickly recognize any policy deviations to intercede early and give remediation or retraining before a human blunder turns into a fundamental issue.

Artificial intelligence likewise gives an incredible tool to fight against business actors or fraudsters to seek to game the framework of government benefits and regulatory enforcement. Neural networks can consistently search out arising patterns that demonstrate another scheme of abuse or signal that a private entertainer may have reverse-engineered government procedures to acquire more good results. Automated risk scoring utilizing machine learning helps focus enforcement resources and guarantee program trustworthiness.

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Effective Governance Requires Implementation of Artificial Intelligence - Analytics Insight

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A curated list of the latest breakthroughs in AI by release date with a clear video explanation, link to a more in-depth article, andcode

Even with everything that happened in the world this year, we still had the chance to see a lot of amazing research come out. Especially in the field of artificial intelligence. More, many important aspects were highlighted this year, like the ethical aspects, important biases, and much more. Artificial intelligence and our understanding of the human brain and its link to AI is constantly evolving, showing promising applications in the soon future.

Here are the most interesting research papers of the year, in case you missed any of them. In short, it is basically a curated list of the latest breakthroughs in AI and Data Science by release date with a clear video explanation, link to a more in-depth article, and code (if applicable). Enjoy the read!

The complete reference to each paper is listed at the end of this repository.

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2020: A Year Full of Amazing AI papers- A Review Machine Learning Times - The Predictive Analytics Times