Cognitive computing is the use of computerized models to simulate the human thought process in complex situations where the answers may be ambiguous and uncertain. The phrase is closely associated with IBM’s cognitive computer system, Watson.

Computers are faster than humans at processing and calculating, but they have yet to master some tasks, such as understanding natural language and recognizing objects in an image. Cognitive computing is an attempt to have computers mimic the way a human brain works.

To accomplish this, cognitive computing makes use of artificial intelligence (AI) and other underlying technologies, including the following:

• Expert systems
• Neural networks
• Machine learning
• Deep learning
• Natural language processing (NLP)
• Speech recognition
• Object recognition
• Robotics

Cognitive computing uses these processes in conjunction with self-learning algorithms, data analysis, and pattern recognition to teach computing systems. The learning technology can be used for speech recognition, sentiment analysis, risk assessments, face detection, and more. In addition, it is particularly useful in fields such as healthcare, banking, finance, and retail.

How Does Cognitive Computing Work?

Systems used in the cognitive sciences combine data from various sources while weighing context and conflicting evidence to suggest the best possible answers. To achieve this, cognitive systems include self-learning technologies that use data mining, pattern recognition, and NLP to mimic human intelligence.

Using computer systems to solve the types of problems that humans are typically tasked with requires vast amounts of structured and unstructured data fed to machine learning algorithms. Over time, cognitive systems are able to refine the way they identify patterns and the way they process data. They become capable of anticipating new problems and modeling possible solutions.

For example, by storing thousands of pictures of dogs in a database, an AI system can be taught how to identify pictures of dogs. The more data a system is exposed to, the more it is able to learn and the more accurate it becomes over time.

To achieve those capabilities, cognitive computing systems must have the following attributes:

• Adaptive. These systems must be flexible enough to learn as information changes and as goals evolve. They must digest dynamic data in real time and adjust as the data and environment change.

• Interactive. Human-computer interaction is a critical component of cognitive systems. Users must be able to interact with cognitive machines and define their needs as those needs change. The technologies must also be able to interact with other processors, devices, and cloud platforms.

• Iterative and stateful. Cognitive computing technologies can ask questions and pull in additional data to identify or clarify a problem. They must be stateful in that they keep information about similar situations that have previously occurred.

• Contextual. Understanding context is critical in thought processes. Cognitive systems must understand, identify and mine contextual data, such as syntax, time, location, domain, requirements, and a user’s profile, tasks, and goals. The systems may draw on multiple sources of information, including structured and unstructured data and visual, auditory, and sensor data.

Examples and applications of cognitive computing

Cognitive computing systems are typically used to accomplish tasks that require the parsing of large amounts of data. For example, in computer science, cognitive computing aids in big data analytics, identifying trends and patterns, understanding human language, and interacting with customers.

Digital wellness (also known as digital wellbeing or digital health) is the pursuit of an intentional and healthy relationship with technology, both in the workplace and in personal life. With many jobs and everyday activities relying on the internet and digital devices, the goal of digital wellness is to promote healthy use habits and assist the user in maintaining a healthy lifestyle in their daily life.

For example, these technologies might add “do not disturb” features that block out focused work hours and silence smartphone notifications, or alert users when their daily screen time has surpassed healthy limits. Other digital wellness technologies focus on improving the employee experience inside a digital workspace. These digital wellness tools include automation and micro apps that eliminate the distraction of routine approval tasks and calendar RSVPs.

1. Take a look at your digital habits

Creating new habits can feel daunting but taking small steps and adjusting to a new way of using your digital devices will help you to be happier and more present. Ask yourself some questions: How do your digital devices make you feel? Do you sometimes feel overwhelmed with too much information or feel pressured or stressed by social media or messages? Maybe you get anxious if you forget your mobile phone when going out? If your digital device is causing you negative feelings, then it’s most probably time to look at how you can improve your digital well-being!

2. Monitor your digital activity

The first step towards improving your digital well-being is to get a detailed understanding of your tech use. It is really important to be aware of how much time you spend using digital devices and how you interact with them. Most smartphones now have the ability to monitor your activity so you can analyze the time you spend on each app and digital device.

3. Set the boundaries

We are surrounded by digital devices. We live in a world of tech! However, we are failing to set healthy tech boundaries. You can set daily limits on the apps and websites you use. Once you hit the limit, the apps and sites pause and notifications are silenced.

4. Bedtime curfew

Disconnect your phone or devices to help you get a better night’s sleep. There are various apps that will put your phone in nighttime mode, silence your notifications and turn your screen to grayscale which minimizes blue light. Exposing ourselves to artificial blue light at bedtime disrupts our natural sleep-wake cycle as it blocks the hormone melatonin which helps us to fall asleep.

5. Gadget-free meal time

Throughout the years, sitting down with the family or your loved ones for an evening meal was the time for busy families and people to come together, relax and chat about their day at school or work. In current times, research shows that mobile phones and electronic gadgets have become part of the family meal resulting in silent meals with little or no communication. Psychologist and behavioral expert Emma Kenny said “Making sure that mealtimes are a technology-free zone is critical to family cohesion and means that every family member can be fully present whilst enjoying a nutritious and delicious shared meal.”

6. Focus mode

It is all too easy to get distracted with app notifications! There are options on some mobile phones to temporarily pause apps. This will prevent your phone from disturbing you when you need to focus on something important. If you try to open an app whilst in focus mode, it will remind you that the app is paused!

There’s no shortage of stories about smart or lucky investors making millions of dollars from well-timed crypto trades, particularly in the pre-winter boom years. The people who built the systems developed the software and founded the companies that those investors use, on the other hand, earned not millions, but billions.

The world of blockchain billionaires is a very small and exclusive fraternity. Not only aren’t there many of them, but their ranks include several partners who both got rich at the same time after co-founding the same company together.

Keep reading to meet the crypto billionaires who made a fortune building the blockchain world that many mainstream Americans are just learning about now.

1. Fred Ehrsam

Fred Ehrsam first learned about digital currency as an avid “World of Warcraft” player. In 2012, he co-founded Coinbase with Brian Armstrong, who also appears on this list. Coinbase went on to become the biggest cryptocurrency brokerage in America.

According to Forbes, Ehrsam still owns 6% of the company and sits on the board despite leaving Coinbase in 2017. One year later in 2018, he founded the crypto investment firm Paradigm.

2. Michael Saylor

Michael Saylor was a billionaire, then he wasn’t, and now he is again. The MIT grad and former rocket scientist founded the business analytics software firm MicroStrategy in 1989. He rode the dotcom wave to a 10-figure net worth until the dotcom bust ended his stint as a billionaire.

According to Forbes, he reclaimed membership in the three-comma club with a well-timed purchase of tens of thousands of bitcoins.

3. Jed McCaleb

Few billionaire crypto pioneers go back as far as Jed McCaleb, who founded Mt. Gox in 2010 as the first legitimate cryptocurrency exchange. Mt. Gox has been a notorious part of crypto folklore since the exchange was hacked in the tumultuous early days of Bitcoin.

McCaleb sold Mt. Gox one year before the hack. Two years later in 2012, he co-founded Ripple with Chris Larsen — more on him shortly — and according to Forbes, that’s where he made his real money. McCaleb received 9 billion XRP as a Ripple founder, and it’s estimated that he still owns 3.4 billion, which represents the bulk of his wealth.

4. Devin Finzer

Blockchain billionaire Devin Finzer made his fortune not in cryptocurrencies, but in NFTs. The CEO and co-founder of the NFT marketplace OpenSea, Finzer previously worked as a software engineer for Pinterest.

In 2021, when investors valued his company at $13.3 billion, Finzer and OpenSea co-founder Alex Atallah became the world’s first NFT billionaires, according to Forbes.

5. Alex Atallah

OpenSea co-founder and CTO Alex Atallah share the title of the world’s first NFT billionaire with fellow co-founder Devin Finzer. Both he and Finzer own an estimated 18% of the $13.3 billion NFT marketplace, according to Forbes.

6. Nikil Viswanathan

Nikil Viswanathan co-founded Alchemy with Joe Lau in 2020, and today, thousands of blockchain and Web3 companies rely on the company’s software. Before founding Alchemy, the duo — both Stanford grads — built Down to Lunch, a meetup app that at one point was No. 1 in the Apple Store.