Basics of Artificial Intelligence and Machine Learning

Aditya Chakurkar | June 22, 2021 | 73 views

Basics of AI and machine learning
Lately, we all often come across two very hot buzzwords — Artificial Intelligence (AI) and Machine Learning (ML). Perhaps the impact of artificial intelligence and machine learning on today’s business world is more than our daily lives.

According to a Bloomberg report, around $300 million were invested in 2014 to promote AI-powered startups. It was 300% more than the previous year’s investment in venture capital.

It’s hard to deny the fact that artificial intelligence and machine learning are all around us. Whether it is about protecting confidential information at work or just playing your favourite games on PS5, AI and ML are there.

Researchers, scientists, computer engineers, and analysts are working hard together to pass on human-like intelligence in machines so that they can think and act according to real-life scenarios.

Businesses have changed their approach to AI keeping enterprise adoption in mind rather than treating it as just a research topic. Tech giants such as Google, Facebook, Microsoft have already invested billions in Artificial Intelligence and Machine Learning and already have started to reshape the customer experience.

But the AI and ML incorporation we see today is just the tip of an iceberg. In the coming years, you will see them take over products and services one after another.

What Is Artificial Intelligence and Machine Learning?

It is nowadays common to see several companies marketing themselves as AI-powered startups even though their operations don’t really revolve around AI.

To understand this type of gimmicky marketing, it is essential to first understand what Artificial Intelligence and Machine Learning are.

Let’s be clear in the beginning about one fact — AI and ML are not the same things. If you think they are, kill this perception before it makes things very confusing.

Both these terms crop up especially when the discussion is about the use of Artificial Intelligence in marketing, the use of Machine Learning in marketing, analytics, Big Data, and the modern-day tech that is transforming the world.

To ease down the learning, here’s the best answer:

Artificial Intelligence is a science used to develop systems that can mimic decision-making and behaviour like humans. In simple words, the main application of Artificial Intelligence is to make intelligent machines.

Machine Learning is the subset of artificial intelligence that uses data to perform tasks. It involves designing and applying the data models or algorithms that can learn from their past experiences.

There’s a subset of Machine Learning, too — Deep Learning. It counts on multilayered neural networks to perform tasks.

Early Days of Artificial Intelligence

The early mentions of AI trace back to Greek mythologies that have stories of a mechanical man that could mimic our own behaviour.

Plus, the early computers were termed as “logical machines'' in Europe. These machines could solve arithmetic operations and even store memory. Scientists, fundamentally, were inspired by them to create mechanical brains.

Over time, technology got more and more modern. And, our understanding of how the human mind works improved. Both these factors lead to the current AI revolution.

Today, the use of AI is more focused on mimicking the decision-making process of humans rather than performing complex calculations. The prime motive of this is to allow machines to think and act more like humans.

AI-powered machines that are designed to act intelligently come into two basic groups — General AI and Applied AI.

General AIs are relatively less common and can theoretically handle any task. The most exciting improvements in the field of AI are happening in this specific area. In fact, it’s generalized AI that led to the rise of Machine Learning.

On the other hand, applied AIs are designed to perform relatively smaller tasks like smartly trading shares and stocks, or guiding an autonomous vehicle to its destination, etc.

The Rise of Machine Learning

As mentioned earlier, Machine Learning is a subset of AI and can also be treated as the current state-of-the-art. It came into reality primarily because of the two major breakthroughs — the rise of the internet and human realization.

In 1959, an American pioneer in the field of computer gaming and AI, Arthur Samual, realized that it can be possible to teach machines how to learn to perform tasks themselves rather than us telling them how to.

As long as the emergence of the internet is concerned, that helped scientists with tons of digital information that could be analysed for the betterment of AI and eventually, ML.

After these innovations, it was more efficient for scientists and engineers to program machines in a way that they learn to think like humans and then connect them to the internet so that they have all the needed information.

Vertical AI And Horizontal AI

No matter what kind of AI research it is, knowledge engineering is its essential part. Machines need plenty of information to think and act like humans. Therefore, AI needs access to objects, categories, properties, and relations between them to apply knowledge engineering.

AI is responsible for generating analytical reasoning power, problem-solving abilities, and common sense in machines. And, it is not an easy task!

The way AI serves us can be divided into two parts — Vertical AI and Horizontal AI.

Vertical AI is used to perform single jobs such as automating repetitive tasks, scheduling meetings, etc. Vertical AI bots are so accurate in performing a single job that people often mistake them for human beings.

Horizontal AI, on the other hand, can handle more than one task at the same time. The best examples of horizontal AI are Alexa, Siri, and Cortana.

Different Types of Machine Learning

ML can be best used to fix complex tasks such as enabling self-driving cars, face recognition, credit card fraud detection, etc. It uses huge, complex algorithms that keep on iterating frequently over big data sets.
The following are the 3 major Machine Learning areas:

● Reinforcement Learning
● Unsupervised Learning
● Supervised Learning


Reinforcement Learning

In reinforcement machine learning, algorithms allow machines and software agents to automate ideal behaviour within a particular context to improve the performance of an overall system.

It is characterised by learning problems rather than learning methods. If any method can solve a problem, it can be a reinforcement learning method. This Machine Learning technique assumes that the dynamic environment is connected to a software agent such as a computer program, bot, or robot. Ultimately, it chooses a specific action in order to rapidly deliver the most efficient result.


Unsupervised Learning

Due to the involvement of unclustered data, unsupervised machine learning is more complex than others. With it, the machine has to learn independently without any supervision.

No fixed or correct solution is provided for any problem in this technique. The algorithm has to identify the data patterns and find the solution.

The recommendation engines we see on several eCommerce websites and Facebook friend requests suggestions are the best examples of this sort of Machine Learning.


Supervised Learning

Training datasets are used in supervised learning. The algorithms are created in such a way that they can analyse the data patterns and develop an inferred function.

The produced correct solution is then used to map new examples. The best example of supervised machine learning is credit card fraud detection.


Final Words

Artificial Intelligence and Machine Learning never fall short to surprise us with their exciting innovations. Their impact has reached all the industries including eCommerce, customer service, finance, education, healthcare, pharma, infrastructure security, and whatnot. Needless to say, all these industries are very keen on reaping all the benefits of Artificial Intelligence and Machine Learning.

The human-like AI was an inevitable thing as most technologists thought. Today, we are indeed closer to this goal than ever. This exciting journey in the past couple of years is the result of how we predict AL and ML works.

FAQs

Why is AI Marketing important?

With AI marketing, businesses and marketers can analyse and consolidate a large amount of data from emails, social media, and other platforms faster. The achieved insights can be used to improve campaign performance and eventually boost the returns on investment in a relatively lesser time.

AI marketing is the best and the most efficient way to eliminate the risks of human errors while optimizing and streamlining the campaigns more effectively. The following benefits of AI marketing justify the attention it has received all over the world.

��� A better understanding of your consumers
● Optimization of digital advertising campaigns
● Offer comprehensive customer profiles
● Allow real-time interactions with consumers
● Refined content delivery
● Reduced marketing costs
● Improved ROI

Is artificial intelligence and machine learning the same?

The straight answer to this question is NO. They are not the same thing.
AI allows machines to learn human behaviour while ML is the subset of AI that teaches machines to learn on their own with the help of past data.

Does AI need machine learning?

Fundamentally, ML is not required for AI as AI systems do not need to be pre-programmed. Instead of such software agents, they get help from algorithms that can use their own intelligence to solve queries. These can be Machine Learning algorithms such as Deep Learning neural networks and Reinforcement Learning algorithms.

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Vendr Launches 2.0, The Most Complete SaaS Buying Platform on The Market

Vendr | August 10, 2022

Vendr, the world’s first SaaS buying platform, today announced the launch of Vendr 2.0, the most complete SaaS buying platform on the market. SaaS is a top-three line item expense, but most companies aren’t getting the appropriate return on their software investment. Vendr 2.0 harnesses Vendr’s SaaS purchasing and SaaS management products, combining the power of seasoned negotiators armed with insights from over 13,000 deals alongside robust software featuring an integrated system of record. Now, enterprise customers will be equipped with an unprecedented level of visibility into which software their teams are buying and using — in one central location. This enables leaders to reduce overspend and eliminate duplicative products. Most importantly, it unlocks insights that lead to better software choices and faster procurement at lower prices. The launch comes on the heels of the company’s recent ​​$150MM Series B, co-led by return investor Craft Ventures and new investor SoftBank Vision Fund 2––which brought the company into Unicorn status––and its acquisition of SaaS management company Blissfully earlier this year. “The software purchasing process is broken and becoming all the more cumbersome as companies everywhere work to cut costs, as they seek to do more with less. “The introduction of Vendr 2.0 enables organizations to manage their second-highest expense––software––more effectively than ever before, while reducing the difficulties surrounding the process. Vendr 2.0 aims to be the most complete, no-brainer, SaaS buying platform on the market –– and one that pays for itself.” Ryan Neu, Vendr CEO and co-founder The standard buying process historically wastes time and resources for both software vendors and customers. Vendr enables businesses to maximize the return on their SaaS investments through cost savings and more efficient spend, improving stack visibility across the organization. Composed of the best industry data of more than 2,000 SaaS suppliers, Vendr 2.0 is facilitating critical transformation in how organizations purchase and manage software. Tapping Into Transparency Software buying is a perpetual process and it no longer makes sense to have buying and supplier lifecycle management exist in disparate places. By bringing everything into one place, companies layer the benefits of an expert service team and deep SaaS insights into an integrated system of record that offers unparalleled visibility into their stack. Using Vendr, customers can take a proactive approach to their SaaS spend, equipping their teams with the best software while saving money. Buyer <-> supplier: Vendr offers insights and negotiation support to help buyers and sellers quickly evaluate whether a deal is fair for both sides, ensuring that the process continues moving along internally once it comes time to buy. Buyer <-> procurement function: Vendr provides visibility into internal approval workflows and offers fast-tracked ways to request purchases, leading to smoother relationships between buyers and their company procurement functions. Finance/procurement <-> department heads: With better visibility and faster purchase cycles, stakeholders can easily see the value-add of finance and procurement, ensuring compliance and keeping a handle on costs, leading to better business outcomes for all. This new platform builds upon the competitive advantages that Vendr has in the market as the category creator with the deepest source of supplier insight––based on thousands of deals––as well as the most seasoned negotiators in the industry. Vendr has processed over $1.5B in customer software spend and delivered over $240M in software savings to its customers. To see how much you could be saving on your annual software expense, get in touch here. About Vendr Vendr is changing how companies find, buy and manage SaaS. The first of its kind, Vendr's SaaS buying platform offers both a product and people-powered service to enable the world's fastest-growing companies to purchase software quickly and with guaranteed savings. Today, Vendr has facilitated over $1.5B+ in SaaS purchases across 2,500+ suppliers for Finance and Procurement teams at HubSpot, Brex, Canva, Reddit, Toast, and more. Headquartered in Boston with a second location in Charleston, Vendr was founded in 2019 by Ryan Neu and co-founders Ariel Diaz and Aaron White, who joined the team through the acquisition of Blissfully in 2022. The company has over 250 employees globally

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SOFTWARE

Workato joins AWS ISV Accelerate Program and AWS Marketplace

Workato | August 12, 2022

Workato, a leading enterprise automation platform, has announced today that it has been accepted into the Amazon Web Services (AWS) Independent Software Vendor (ISV) Accelerate Program, a co-sell program for organizations that provide software solutions that run on or integrate with AWS. The program helps organizations drive new business and accelerate sales cycles by connecting the participating ISVs with the AWS Sales organization. Workato Enterprise Automation Platform is also now available in AWS Marketplace. Through the AWS ISV Accelerate Program, Workato receives focused co-sell support and benefits to connect with AWS field sellers globally, who service millions of active AWS customers. Co-selling provides better customer outcomes and provides mutual commitment from AWS and AWS Partners. AWS Marketplace is a curated digital catalog that customers can use to find, buy, deploy, and manage third-party software, data, and services to build solutions and run their businesses on AWS. Customers can find thousands of software, solutions, and services across a number of categories including security, machine learning, business applications, and more. They can quickly launch pre-configured software, and choose software solutions in Amazon Machine Images (AMIs), software as a service (SaaS), and other formats. “We are beyond excited to join the AWS ISV Accelerate Program, further cementing our position within the enterprise automation space. To pair this with our debut in AWS Marketplace lends itself to our continued commitment to enabling companies to tap into the growth mindset and transform their organization with Workato. “This endeavor allows us to reach new AWS customers and help them reach their fullest potential.” Markus Zirn, Senior Vice President, Strategy & Business Development at Workato Workato is transforming automation across businesses with a single platform for data, apps, and processes and is emerging as a market leader in enterprise automation. Workato is a proven automation platform that allows organizations to build scalable quote-to-cash processes that increase accuracy and speed while reducing human intervention. Enterprises significantly improve their quote-to-cash approach while also providing a better purchasing experience to the end customer. Workato solutions running on AWS allow companies to automate work throughout the entire organization — completely on the cloud. Building on the relationship with AWS, Workato is also helping joint customers solve complex business challenges, starting with Quote-to-Cash. The solution enables organizations to better integrate their tech stack to allow for seamless data transfer and bilateral sync and to automate repeatable processes at scale to further improve efficiency and accuracy. About Workato The leader in enterprise automation, Workato helps organizations work faster and smarter without compromising security and governance. Built for Business and IT users, Workato is trusted by over 17,000 of the world's top brands, including Broadcom, Intuit, and Box. Headquartered in Mountain View, Calif., Workato is backed by Altimeter Capital, Battery Ventures, Insight Venture Partners, Tiger Global, and Redpoint Ventures.

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SOFTWARE

Dataminr Announces New Partners With the Launch of Its Global Partner Program

Dataminr | August 12, 2022

Dataminr, the world's leading real-time information discovery platform, today launched its global partner ecosystem, the Dataminr Partner Program. The program will dramatically expand Dataminr's customer reach across the corporate market, while also providing better enterprise workflow integration and the flexibility to procure Dataminr's products through trusted partners. Dataminr's partner program makes it easier for corporations to operationalize Dataminr's AI Platform across their organization and more seamlessly integrate Dataminr alerts into their workflow. Additionally, this initiative will open up Dataminr's offerings to corporate enterprises in a growing set of commercial sectors and geographic regions through Channel Partners, and provide our signals to Platform Partners to power products for new corporate use cases including supply chain, logistics, fleet management, insurance and many more. "The Dataminr Partner Program broadens our scale and reach through channel partners and reseller networks, delivers more value for our customers, and powers global sales through partners that can sell the Dataminr solution in their local region. "The program will accelerate Dataminr's customer growth, optimize workflow integration, unlock new corporate use cases for our AI Platform, and also feature numerous benefits and incentives for partnerships with comprehensive partner resources." Aharon Weiner, SVP Global Partnerships, Dataminr Leading merchants and businesses including Google, Amazon Web Services, Microsoft, TD SYNNEX, NEC Networks & System Integration Corporation—and long-time partner ESRI—are new participants in the partner ecosystem. "We are proud to have the opportunity to be one of the first participants in the Dataminr Partner Program," said Cheryl Neal, Vice President of New Vendor Acquisition at TD SYNNEX. "Together with Dataminr, we will be able to enrich the breadth and depth of our offerings, ultimately maximizing the value of our customers' information and IT investments and unlocking growth for the future." For new partners, comprehensive program benefits include: Flexible compensation models with competitive margins and margin protection Co-selling benefits such as joint business planning and joint account mapping Market development funds to drive demand and pipeline growth A library of resources that includes training and enablement, sales tools, marketing assets and more. ABOUT DATAMINR Dataminr delivers the earliest warnings on high impact events and critical information far in advance of other sources. Recognized as one of the world's leading AI businesses, Dataminr enables faster response, more effective risk mitigation and stronger crisis management for public and private sector organizations spanning global corporations, first responders, NGOs, and newsrooms. Recently valued at $4.1B, Dataminr is one of New York's top private technology companies, with 900+ employees across eight global offices.

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FUTURE TECH

Vendr Launches 2.0, The Most Complete SaaS Buying Platform on The Market

Vendr | August 10, 2022

Vendr, the world’s first SaaS buying platform, today announced the launch of Vendr 2.0, the most complete SaaS buying platform on the market. SaaS is a top-three line item expense, but most companies aren’t getting the appropriate return on their software investment. Vendr 2.0 harnesses Vendr’s SaaS purchasing and SaaS management products, combining the power of seasoned negotiators armed with insights from over 13,000 deals alongside robust software featuring an integrated system of record. Now, enterprise customers will be equipped with an unprecedented level of visibility into which software their teams are buying and using — in one central location. This enables leaders to reduce overspend and eliminate duplicative products. Most importantly, it unlocks insights that lead to better software choices and faster procurement at lower prices. The launch comes on the heels of the company’s recent ​​$150MM Series B, co-led by return investor Craft Ventures and new investor SoftBank Vision Fund 2––which brought the company into Unicorn status––and its acquisition of SaaS management company Blissfully earlier this year. “The software purchasing process is broken and becoming all the more cumbersome as companies everywhere work to cut costs, as they seek to do more with less. “The introduction of Vendr 2.0 enables organizations to manage their second-highest expense––software––more effectively than ever before, while reducing the difficulties surrounding the process. Vendr 2.0 aims to be the most complete, no-brainer, SaaS buying platform on the market –– and one that pays for itself.” Ryan Neu, Vendr CEO and co-founder The standard buying process historically wastes time and resources for both software vendors and customers. Vendr enables businesses to maximize the return on their SaaS investments through cost savings and more efficient spend, improving stack visibility across the organization. Composed of the best industry data of more than 2,000 SaaS suppliers, Vendr 2.0 is facilitating critical transformation in how organizations purchase and manage software. Tapping Into Transparency Software buying is a perpetual process and it no longer makes sense to have buying and supplier lifecycle management exist in disparate places. By bringing everything into one place, companies layer the benefits of an expert service team and deep SaaS insights into an integrated system of record that offers unparalleled visibility into their stack. Using Vendr, customers can take a proactive approach to their SaaS spend, equipping their teams with the best software while saving money. Buyer <-> supplier: Vendr offers insights and negotiation support to help buyers and sellers quickly evaluate whether a deal is fair for both sides, ensuring that the process continues moving along internally once it comes time to buy. Buyer <-> procurement function: Vendr provides visibility into internal approval workflows and offers fast-tracked ways to request purchases, leading to smoother relationships between buyers and their company procurement functions. Finance/procurement <-> department heads: With better visibility and faster purchase cycles, stakeholders can easily see the value-add of finance and procurement, ensuring compliance and keeping a handle on costs, leading to better business outcomes for all. This new platform builds upon the competitive advantages that Vendr has in the market as the category creator with the deepest source of supplier insight––based on thousands of deals––as well as the most seasoned negotiators in the industry. Vendr has processed over $1.5B in customer software spend and delivered over $240M in software savings to its customers. To see how much you could be saving on your annual software expense, get in touch here. About Vendr Vendr is changing how companies find, buy and manage SaaS. The first of its kind, Vendr's SaaS buying platform offers both a product and people-powered service to enable the world's fastest-growing companies to purchase software quickly and with guaranteed savings. Today, Vendr has facilitated over $1.5B+ in SaaS purchases across 2,500+ suppliers for Finance and Procurement teams at HubSpot, Brex, Canva, Reddit, Toast, and more. Headquartered in Boston with a second location in Charleston, Vendr was founded in 2019 by Ryan Neu and co-founders Ariel Diaz and Aaron White, who joined the team through the acquisition of Blissfully in 2022. The company has over 250 employees globally

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