Top 10 AI trends in 2021
What is AI?
According to IBM cloud Education definition of AI- Artificial intelligence enables computers and machines to mimic the perception, learning, problem-solving, and decision-making capabilities of the human mind. In computer science, the term artificial intelligence (AI) refers to any human-like intelligence exhibited by a computer, robot, or other machine. In popular usage, artificial intelligence refers to the ability of a computer or machine to mimic the capabilities of the human mind — learning from examples and experience, recognizing objects, understanding and responding to language, making decisions, solving problems — and combining these and other capabilities to perform functions a human might perform, such as greeting a hotel guest or driving a car.
After decades of being relegated to science fiction, today, AI is part of our everyday lives. The surge in AI development is made possible by the sudden availability of large amounts of data and the corresponding development and wide availability of computer systems that can process all that data faster and more accurately than humans can. AI is completing our words as we type them, providing driving directions when we ask, vacuuming our floors, and recommending what we should buy or binge-watch next. And it’s driving applications — such as medical image analysis — that help skilled professionals do important work faster and with greater success.
As common as artificial intelligence is today, understanding AI and AI terminology can be difficult because many of the terms are used interchangeably; and while they are actually interchangeable in some cases, they aren’t in other cases. What’s the difference between artificial intelligence and machine learning? Between machine learning and deep learning? Between speech recognition and natural language processing? Between weak AI and strong AI? This article will try to help you sort through these and other terms and understand the basics of how AI works.
2020 breakthroughs in the field of AI
According to a blog kdnugget In 2020 we saw two big achievements in the race towards true artificial intelligence. OpenAI introduced GPT-3, and Google’s DeepMind released AlphaFold 2. Both of these organizations are racing to research, create and advance the role of artificial intelligence within our society. There are many others making advancements in AI, but GPT-3 and AlphaFold 2 were two of the most notable in 2020.
Human-Computer Interaction is now further along thanks to GPT-3, which can allow us to converse with computers regarding more specialized topics. For AlphaFold 2, 2020 was the year in which the world was engulfed in the COVID-19 pandemic and hundreds of pharmaceutical giants were on a mission to find a vaccine. AlphaFold 2 could very well be what helps scientists get there faster, and to help them understand diseases more quickly on a molecular level which will help to save future live
Language Processing with GPT-3
With GPT-3, scientists were able to train an AI model to converse with humans, and to read and write texts. This astounding development was GPT-3 (aka, Generative Pre-trained Transformer 3) developed by OpenAI. For years people have been fascinated with talking to humanoid robots in their native language, and believe this to be a critical milestone to reach with AI. GPT-3 can process texts in many languages better than its predecessor GPT-2, thanks to its model having 175 billion parameters (the values that a neural network tries to optimize during training), compared with GPT-2’s now meager 1.5 billion.
A 50 Year Challenge Broken with AlphaFold 2
Scientists from Google’s DeepMind were able to create AlphaFold 2 which has been hyped to be one of the biggest breakthroughs in the field of medical science and biology. The model can detect and derive the 3D protein structures of amino acids which could potentially increase the rate at which humans can understand diseases and increase the rate of pharmaceutical manufacturing. Never before in the last century has it been more important for the field of medicine. AI is perfect for assisting in the medical industry: modeling proteins on a molecular level; comparing medical images and finding patterns or anomalies faster than a human; and countless other opportunities to advance drug discovery and clinical processes. Scientists can spend days, months and even years trying to understand the DNA of a new disease, but can now save time with an assist from AI. Breakthroughs like AlphaFold 2 need to continue for us to advance our understanding in a world filled with so much we have yet to understand
Top Artificial Intelligence trends in 2021(according to mygreatlearning.com)
The focus of AI adoption is restricted to improving the efficiency of operations or the effectiveness of operations. It can be leveraged to improve the stakeholder experience as well. Let us take a look at the top trends expected in 2021.
1. Greater Cloud and AI collaboration
Rico Burnett, the director of client innovation at legal services provider Exigent, says that Artificial Intelligence will play a significant role in the broad adoption of Cloud Solutions in 2021. Through the deployment of artificial intelligence, it will be possible to monitor and manage cloud resources and the vast amount of available data.
2. AI solutions for IT
The number of AI solutions that are being developed for IT will increase in 2021. Capgemini’s Simion predicts that AI solutions that can detect common IT problems on its own and self-correct any small malfunctions or issues will see an increase in the upcoming years. This will reduce downtime and allow the teams in an organisation to work on high-complexity projects and focus elsewhere.
3. AIOps becomes more popular
Over the last few years, the complexity of IT systems has increased. Forrester recently said that vendors would want platform solutions that combine more than one monitoring discipline such as application, infrastructure, and networking. IT operations and other teams can improve their key processes, decision making, and tasks with AIOps solutions and improved analysis of the volumes of data coming its way. Forrester advised the IT leaders to find AIOps providers who will empower the cross-team collaboration through end-to-end digital experiences, data correlation, and integration of the IT operations management toolchain.
4. AI will help in structuring data
In the future, we will see more unstructured data is structured with natural language processing and machine learning processes. Organisations will leverage these technologies and create data that RPA or robotic process automation technology can use when they want to automate transactional activity in an organisation. RPA is one of the fastest-growing areas in the software industry. The only limitation that it faces is that it can only use structured data. With the help of AI, unstructured data can easily be converted into structured data, which can provide a defined output.
5. Artificial intelligence talent will remain tight
The supply of talent is expected to be an issue in adopting artificial intelligence in 2021. There has been a persistent gap in AI talent, and organisations have finally realised this potential. It is essential to address this gap and ensure that a wider group of people learn artificial intelligence. Ensuring that a broader set of users have access to artificial intelligence to focus on technology, learning strategies, and supporting a change in the working environment is essential in 2021.
6. Large scale adoption of AI in the IT industry
We have seen continuous growth in adoption of AI within the IT industry. However, Simion predicts that organisations will use AI in production and start using them at a large scale. With the help of artificial intelligence, an organisation can get ROI in real-time. This means that organisations will see their efforts being paid off.
7. AI Ethics is the focus
Natalie Cartwright, co-founder and COO of Finn AI, an AI banking platform, predicts that in 2021, organisations will deliver expertise on how to leverage artificial intelligence against major global problems, stimulate innovation and economic growth, and ensure inclusion and diversity. As AI ethics become more important to organisations, transparency of data and algorithm fairness are two of the issues that are in the spotlight.
8. Augmented Processes become increasingly popular
Artificial intelligence and data science will prove to be a part of a bigger picture when it comes to innovation and automation in 2021. Data ecosystems are scalable, lean, and also provide data on time to heterogeneous sources. However, it is necessary to provide a foundation to adapt and foster innovation. According to Ana Maloberti, a big data engineer at Globant, companies will go a step further in optimising their augmented business and development processes. Using Artificial Intelligence, software development processes can be optimised, and we can look for a wider collective intelligence and improved collaboration. We must foster a data-driven culture and grow out of the experimental stages to move into a sustainable delivery model.
9. Artificial Intelligence will become more explainable
The senior director of product at customer data hub Tealium, Dave Lucas, says that there will be a bigger focus on explainability. As more data regulations come into play, the trust in AI will be pivotal. To clearly understand and articulate how each characteristic will contribute to the end prediction or the result of the machine learning model.
10. Voice and Language Driven intelligence
Particularly in customer care centres, the increase in remote working has driven a great opportunity to adopt NLP or ASR (automated speech recognition) capabilities. Less than 5% of all customer contacts are routinely checked for quality feedback according to ISG’s Butterfield. Due to the lack of one-on-one coaching, organisations can use artificial intelligence to complete routine quality checks on customer understanding and intent to ensure continued compliance
