‘Artificial Intelligence (AI)- we need more of that’ is the underlying statement every C-level executive reads in the newspaper, hears at every meeting, and thinks during every innovation. The moments of truth in the ever-growing technology is still haunting many spaces and yet building path for innovations.
When we look at the history of AI, it took us more than 60 years to reach this techno-advancement stage. MANIAC, developed at Los Alamos Scientific Laboratory in 1956, was the first computer to defeat a human in a chess game. Over the years, AI developed, faulted, but remained as one of the most pivotal technologies of all time.
Let’s see how AI has been performing in 2019
According to the Allen Institute of Artificial Intelligence, China is not just overtaking in the sheer volume of data, but even in the domain of production of high-impact papers measured by top 50%, 10%, and 1% most cited papers.
If the current estimates go further, China will have more top 10% papers by 2020 and more top 1% papers by 2025. Though in 2018, the US overtook China in terms of investments in AI, AI research and amp; development has become the new battlefield for businesses and countries.
If we look at the AI adoption for businesses, 73% of the senior executives see AI/Machine Learning (ML) as the area they want to maintain or increase investment in. Out of which, only 33% want to invest more in getting better visibility of their processes, but they have not factored in the understanding of the current processes and technologies that can help their businesses grow, according to Celonis. While over 71% of the US enterprises are planning to leverage more of AI and ML tools for security, 49% IT professionals agreed to be extremely comfortable in using these tools. Moreover, 76% don’t care if their company is actually leveraging the technology, whereas 56% are sure about what exactly AI and ML means, according to Webroot.
Innovative AI Applications in 2019
- Home robot
Homemakers always felt that cleaning is one of the most tedious tasks. And then came vacuum cleaners, which needed human assistance. iRobot Roomba is a smart robotic vacuum cleaner that uses AI to scan the room size, identify obstacles, and even record the most efficient routes taken for cleaning. This AI solution is a self-deploying robot and needs no human assistance during cleaning.
PathAI offers a pathology tool that accesses tissue samples and predicts an accurate diagnosis. Developed for the pathologists, it helps improve the diagnostic accuracy and the treatment methods. The tool was created to form a process for advanced diagnostics and be made available to all the regions. PathAI worked with Bill and amp; Melinda Gates Foundation and Philips to develop high-volume prognostic test support tools and plans for sustainable access to their advanced diagnostic services.
- Customer service
Chatbots are already reshaping our customer service with its advanced analytics and natural language processing. By 2020, it’s estimated that there would be 63% of AI bots deployed in combination with human customer service representatives. Bots will not replace the human representatives; they will make them more efficient.
One of the most efficient chatbots that have impacted customer service in 2019 is ChatBot. It provides template-based AI chatbot functions and implements different scenarios to assist customers to learn about the new queries. Businesses can even improve the ChatBot using training tools powered by ML.
Tesla is by far the winner in implementing AI in the automobile industry. In August this year, the company redesigned its AI chips, making them efficient and better. It provided all the self-driving capabilities, with 20% reductions. Each of the AI chip runs with 2GHz speed and performs 36 trillion operations per second. The car is powered by 2 chips, and results from both are compared. The decisions are then taken by a computer, and the function is performed if the chip agrees.
LogRhythm provides an end-to-end security solution for businesses analyzing, detecting, and responding to threats at a much faster pace. The tools use ML to profile and detect a) threats, b) compromised accounts, c) privilege abuse, and d) other security issues, which can result in a threat. A dashboard-based solution allows the security teams to easily and quickly respond to threats.
How does the future of AI looks like hereon
According to Forrester, 53% of global data and analytics decision-makers stated that they have already implemented, are in the process of expanding, or are upgrading their AI implementation. Over the past 1 year, 29% of global developers have worked with the AI and ML software. Using edge computing, 54% of the global mobility decision-makers are anticipating that they will be able to handle present and future AI demands. About 16% of global B2C leaders are planning to increase their spending on data and analytics technology.
AI is still in demand…
Though if we go far into the future, the applications will be endless and the prospects unending. So take a step toward 2020 and see what will be possible next year:
- Utility robot
It is a robot that can replace the human on the basis of all functionalities and intelligence.
It was a big challenge when the inventors imagined building a robot that can act and think like a human. Yet we devised a robot that is functional enough to do certain tasks. Boston Dynamics developed SPOT, a nimble robot that can climb stairs and traverse through rough terrain. Massachusetts State Police recently tested the robot to open doors to check the potential of these robots to assist human officers during hostage situations.
- Virtual assistant
Alexa, can you please schedule a meeting for tomorrow.
Virtual assistants from Google and Amazon have been on the forefront, giving effective no-touch solutions to consumers, ranging from wider connectivity to different functions. Personalization, security of users’ privacy, and cross-platform connectivity for users will be the next step for businesses building virtual assistants.
- Face identification
Smartphones have already implemented the face ID technology, but they do come with certain glitches of their own. In 2020, businesses will explore the face ID technology to improve the customer experience. AI-driven applications will allow the machine to recognize the user’s face and complete the transaction.
- Analyzing data
During the deadly mass shooting recently, social media sites such as Facebook, Twitter, and Snapchat became a line of live coverage, but many of them were fake. AI-powered analytics tools could be taught to determine whether the headline agrees with the article body, process text, analyze the writing style, and helps image forensics to detect the image authenticity. The ratio of reactions versus shares on Facebook will assist in determining the popularity of the article, apart from correlating the new data from other data on the website and determining anomalies.
- Neural network
A human brain communicates using neurons to send signals and communicate, and the body performs a different function when the signals are communicated across nerves using neurons. The complicated setup of signaling systems is analyzed to create an artificial neural network. Text classification is an essential application with focus on web searching, information filtering, and sentiment analysis. Named Entity Recognition (NER) is to classify terms based on entities, so it becomes easier for text readers to define terms.
AI has evolved over the decades, but its usability still remains in question. The challenge for businesses is to identify processes where AI application can be implemented not only as a technology but as a performance enhancer. It will be interesting to see how AI will be moving from the small steps of 2019 to taking a giant leap in the coming months.
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