#AI #Trending Tech during 2020
10 Artificial Intelligence Technologies To Look For during 2020
Tech decision-makers are (and should keep) looking for ways to effectively implement artificial intelligence technologies into their businesses and, therefore, drive value. And though all AI technologies most definitely have their own merits, not all of them are worth investing in.
If one thing and only one thing happens after you read this article, we hope it is that you are inspired to join the 62% of companies who boosted their enterprises in 2019 by adopting Artificial Intelligence into their workflow.
1. Speech recognition
One great example: Siri is just one of the systems that can understand you.
Every day, more and more systems are created that can transcribe human language, reaching hundreds of thousands through voice-response interactive systems and mobile apps.
Companies offering speech recognition services include NICE, Nuance Communications, OpenText, and Verint Systems.
2. ChatBot(Virtual Agents)
A virtual agent is nothing more than a computer agent or program capable of interacting with humans.
The most common example of this kind of technology is chatbots.
Virtual agents are currently being used for customer service and support and as smart home managers.
Some of the companies that provide virtual agents include Amazon, Apple, Artificial Solutions, Assist AI, Creative Virtual, Google, IBM, IPsoft, Microsoft, and Satisfi.
3. Machine Learning Platforms
These days, computers can also easily learn, and they can be incredibly intelligent!
Machine learning (ML) is a subdiscipline of computer science and a branch of AI. Its goal is to develop techniques that allow computers to learn.
By providing algorithms, APIs (application programming interface), development and training tools, big data, applications, and other machines, ML platforms are gaining more and more traction every day.
They are currently mainly being used for prediction and classification.
Some of the companies selling ML platforms include Amazon, Fractal Analytics, Google, H2O.ai, Microsoft, SAS, & Skytree.
The last one is the first and only audience management tool in the world that applies real AI and machine learning to digital advertising to find the most profitable audience or demographic group for any ad.
4. Deep Learning Platforms
Deep learning platforms use a unique form of ML that involves artificial neural circuits with various abstraction layers that can mimic the human brain, processing data, and creating patterns for decision making.
It is currently mainly being used to recognize patterns and classify applications that are only compatible with large-scale data sets.
Deep Instinct, Ersatz Labs, Fluid AI, MathWorks, Peltarion, Saffron Technology, and Sentient Technologies all have deep learning options worthy of exploring.
5. Robotic Processes Automation
Robotic processes automation uses scripts and methods that mimic and automate human tasks to support corporate processes.
It is particularly useful for situations when hiring humans for a specific job or task is too expensive or inefficient.
Again, a good example of this is Adext AI, a platform that automates digital advertising processes using AI, saving businesses from devoting hours to mechanical and repetitive tasks.
It’s a solution that lets you make the most of your human talent and move employees into more strategic and creative positions, so their actions can make an impact on the company’s growth.
Advanced Systems Concepts, Automation Anywhere, Blue Prism, UiPath, and WorkFusion are other examples of robotic processes automation companies.
6. Cyber Defense
Cyber defense is a computer network defense mechanism that focuses on preventing, detecting, and providing timely responses to attacks or threats to infrastructure and information.
AI and ML are now being used to move cyberdefense into a new evolutionary phase in response to an increasingly hostile environment: Breach Level Index detected a total of over 2 billion breached records during 2017. Seventy-six percent of the records in the survey were lost accidentally, and 69% were an identity theft type of breach.
Recurrent neural networks, which are capable of processing sequences of inputs, can be used in combination with ML techniques to create supervised learning technologies, which uncover suspicious user activity and detect up to 85% of all cyber attacks.
Startups such as Darktrace, which pairs behavioral analytics with advanced mathematics to automatically detect abnormal behavior within organizations and Cylance, which applies AI algorithms to stop malware and mitigate damage from zero-day attacks, are both working in the area of AI-powered cyber defense.
DeepInstinct, another cyber defense company, is a deep learning project named “Most Disruptive Startup” by Nvidia’s Silicon Valley ceremony, which protects enterprises’ endpoints, servers, and mobile devices.
Compliance is the certification or confirmation that a person or organization meets the requirements of accepted practices, legislation, rules and regulations, standards, or the terms of a contract, and there is a significant industry that upholds it.
We are now seeing the first wave of regulatory compliance solutions that use AI to deliver efficiency through automation and comprehensive risk coverage.
Some examples of AI’s use in compliance are showing up across the world. For example, NLP (Natural Language Processing) solutions can scan regulatory text and match its patterns with a cluster of keywords to identify the changes that are relevant to an organization.
Capital stress testing solutions with predictive analytics and scenario builders can help organizations stay compliant with regulatory capital requirements. And the volume of transaction activities flagged as potential examples of money laundering can be reduced as deep learning is used to apply increasingly sophisticated business rules to each one.
Companies working in this area include Compliance.ai, a Retch company that matches regulatory documents to a corresponding business function; Merlon Intelligence, a global compliance technology company that supports the financial services industry to combat financial crimes, and Socure, whose patented predictive analytics platform boosts customer acceptance rates while reducing fraud and manual reviews.
8. Content Creation
Content creation now includes any material people contribute to the online world, such as videos, ads, blog posts, white papers, infographics, and other visual or written assets.
Brands like USA Today, Hearst and CBS, are already using AI to generate their content.
Wibbitz, a SaaS tool that helps publishers create videos from written content in minutes with AI video production technology, is a great example of a solution from this field. Wordsmith is another tool, created by Automated Insights, that applies NLP (Natural Language Processing) to generate news stories based on earnings data.
9. Image Recognition
Image recognition is the process of identifying and detecting an object or feature in a digital image or video, and AI is increasingly being stacked on top of this technology to great effect.
AI can search social media platforms for photos and compare them to a wide range of data sets to decide which ones are most relevant during image searches.
Image recognition technology can also be used to detect license plates, diagnose disease, analyze clients and their opinions and verify users based on their faces.
Clarifai provides image recognition systems for customers to detect near-duplicates and find similar uncategorized images.
SenseTime is one of the leaders in this industry and develops face recognition technology that can be applied to payment and picture analysis for bank card verification and other applications. And GumGum’s mission is to unlock the value of images and videos produced across the web using AI technology.
10. Marketing Automation
Marketing divisions have benefitted so much from AI so far, and there is great faith placed in AI within this industry for good reason. Fifty-five percent of marketers are sure AI will have a greater impact in their field that social media has. What a statement.
Marketing automation allows companies to improve engagement and increase efficiency to grow revenue faster. It uses software to automate customer segmentation, customer data integration, and campaign management, and streamlines repetitive tasks, allowing strategic minds to get back to doing what they do best.
One of the leaders in this field is Adext AI, whose audience management platform can boost ad spend efficiency by up to +83% % in just 10 days. The software automates all the process of campaign management and optimization, making daily adjustments per ad to super-optimize campaigns and managing budgets across multiple platforms and over several different demographic and micro demographic groups per ad.