Top 10 Artificial Intelligence Trends in 2022 | AI Trends
- By Rajalekshmy KR
- Artificial Intelligence
Beyond essential AI skills like natural language modelling and self-supervised learning, 2022 will be a landmark year for scientific breakthroughs like Protein identification and developer tools like Copilot.
As a result of these mind-blowing discoveries, many people now have high hopes for artificial intelligence (AI) and are eager to learn more about the future. As a result, this essay will focus on some of the most significant advancements in artificial intelligence (AI), which are expected to increase its power and effect.
AI is becoming necessary for businesses as they automate and analyse COVID-affected datasets. Companies have been more digitally linked since the lockdown and work-from-home policies.
What will the future of artificial intelligence and machine learning look like in 2022?
It will be necessary for IT and business executives to build a strategy for aligning artificial intelligence (AI) with employee interests and corporate goals to reap the full benefits of AI and machine learning developments.
These challenges should be addressed: how to simplify and democratise access to AI, address concerns about the ethical and responsible use of AI, and guarantee AI implementations deliver on the hype.
The following are the top 10 AI trends to keep an eye out for in 2022:
1. Greater Cloud and AI collaboration
Regarding Cloud Solutions, Exigent's Rico Burnett believes that Artificial Intelligence will be an essential factor by 2021. Artificial intelligence will make it feasible to track and handle massive amounts of data on the cloud.
2. More Power to Language Modeling
Machine translation, speech recognition, handwriting recognition, question answering, and information retrieval are examples of language modelling applications.
Because of GPT-3, the most sophisticated language model created by OpenAI, the company has been in the spotlight. GPT-3, for example, has been shown to develop creative fiction, usable computer code, and insightful business memoranda, giving correct human stimulation.
You may expect more advancements in language modelling and applications like automated programme creation in 2022, thanks to OpenAI's GPT-4 and other significant corporations creating strong language models.
3. Automated machine learning (AutoML)
Among the benefits of automated machine learning are enhanced tools for labelling data and automatic tweaking of neural net topologies, says Michael Mazur, CEO of AI Clearing.
As a result of the increased need for adequately labelled data, nations like India, Central Eastern Europe, and South America have sprouted labelling industries employing low-wage workers.
The market began looking for alternatives to hiring offshore workers to prevent or minimise these dangers. Because of advancements in semi- and self-supervised learning, firms may reduce the quantity of data they need to categorise manually.
Artificial Intelligence (AI) will become more affordable and faster to market if selecting and adjusting neural network models is made more automated.
Gartner's future developments include enhancing platform operations, machine learning operations, and data operations to operationalise these models. Xps is Gartner's term for these new capabilities.
4. Conversational AI
Conversational AI is an artificial intelligence that enables speech-based interactions between users and platforms, particularly at scale. To build it, you'll need tools like voice commands, speech synthesis, language processing, and machine learning.
ReportLinker predicted that by 2026, the conversational AI industry would expand from a current value of $6.8 billion to $18.4 billion. The main drivers for this problem are AI-enabled customer support services, omnichannel strategy, constant client interaction, and chatbots' growing demand during COVID-19 constraints.
We should expect to see advancements in conversational AI systems due to the growing demand.
5. AI-Based Cybersecurity
The World Economic Forum recently identified cybercrime as a critical threat to the global economy and called on countries to work together to combat it.
Whenever we use a machine, we put ourselves at greater risk of being a cyberattack victim. This is because every device linked to the internet provides an attack vector. As connected devices get more complex, it becomes increasingly difficult to identify and fix the existing security gaps. Artificial intelligence (AI) can play a critical role in spotting suspect activity by examining trends in network traffic.
As a result, by 2022, we should expect significant advancements in applying artificial intelligence (AI) to cybersecurity.
6. Voice and Language Driven intelligence
For example, in customer service centers, the rise of remote working has provided an excellent chance to implement NLP or ASR (automatic speech recognition) capabilities. ISG's Butterfield consistently evaluates less than 5% of all client contacts for quality feedback. Companies can utilise AI to do frequent quality checks on customer knowledge and intent because one-on-one coaching is unavailable.
7. AI will help in structuring data
More unstructured data will be organised using NLP and machine learning in the future. RPA, or robotic process automation, may automate a company's transactional activities using the data that organisations generate using these technologies. RPA (Robotic Process Automation) is one of the fastest-growing software categories.
With AI, unstructured data may be transformed into structured data that can be used to get a specific result. This is a significant AI development. Because it can only work with structured data, that's the only drawback it has to deal with.
8. Developer Productivity
Artificial Intelligence (AI) is expected to impact the productivity of programmers and developers this year positively.
Amazon Code Guru is one example of an AI-powered development tool that has been used to assist developers in improving the quality of their code and identifying their most expensive lines of code in recent years.
Github and OpenAI cooperated to create Copilot, a tool to aid engineers in designing efficient code. Salesforce has just unveiled its CodeT5 initiative to assist Apex developers in their development.
As a result of recent advancements in language modelling, the coding process from natural language description has become a typical application. OpenAI's Codex is a good illustration of this—and we should expect to see many more similar results in 2017. Tabnine and Ponicode are two further instances of newly invented AI-driven tools for developers.
9. Multi-modal learning
AI increasingly supports text, vision, audio, and IoT sensor data in a single ML model. According to David Talby, owner & CTO of John Snow Labs, a provider of natural language processing tools, developers are beginning to explore novel methods to mix modalities to improve routine activities such as document reading.
Using multi-modal techniques like machine vision and computer vision to train AI algorithms, it is possible to improve medical diagnosis through the better presentation of data. For example, healthcare systems may gather, and process scanned documents such as visual lab results and genetic sequencing reports.
For doctors, this information's arrangement and presentation style might assist them in better comprehending what they're looking at. Using multi-modal approaches will necessitate the hiring or training of data scientists with cross-domain expertise, such as natural language and machine vision.
10. Augmented Processes have become increasingly popular
When it comes to 2023 innovation and automation, artificial intelligence and data science will be a component of a larger picture. There are several advantages to using data ecosystems. They are scalable and lean and give timely data to diverse sources.
The basis for adaptability and creativity must be established. Ana Maloberti, a Globant data engineer, predicts that businesses will improve efficiency. Our collective intelligence and ability to work together are enhanced by using Artificial Intelligence in the software development process. Developing a data-driven culture and moving out of the experimental phase is necessary. This is significant AI development.
11. AI-enabled employee experience
Concerns regarding the impact of artificial intelligence (AI) on human occupations are being raised by IT executives. Howard Brown, founder and CEO of Revenue.io, a call centre tools supplier, says this fuels interest in adopting AI to enhance and augment the staff experience.
Sales and customer success teams, who are already stretched thin and having difficulty filling positions, might benefit significantly from the support of artificial intelligence.
Robotic process automation (RPA) and artificial intelligence (AI) may free sales personnel to have more meaningful conversations with clients by automating repetitive chores. Employee training and coaching might potentially benefit from this technology.
In the previous 12 months, artificial intelligence has seen several significant advancements. Corporations and the developers that work for them will be able to make even more critical advancements in 2022 if they build on this foundation. But talking about AI development for business, you might want to hire the best AI development agency in the US to create the platform.