Category: AI

Where AI Gives a Competitive Edge

On By mehranmuslimiblogIn AILeave a comment

Use of Artificial Intelligence (AI) is growing. According to International Data Corporation (IDC) forecast statistics, spending on the technology will reach $97.9 billion in 2023, which is two and a half times what it was in 2019.

David Schubmahl, IDC research director, said, “The AI market continues to grow at a steady rate in 2019 and we expect this momentum to carry forward,” adding, “The use of artificial intelligence and machine learning (ML) is occurring in a wide range of solutions and applications from ERP and manufacturing software to content management, collaboration, and user productivity. Artificial intelligence and machine learning are top of mind for most organizations today, and IDC expects that AI will be the disrupting influence changing entire industries over the next decade.”

Who is leading AI spending?

According to IDC: “Spending on AI systems will be led by the retail and banking industries, each of which will invest more than $5 billion in 2019. Nearly half of the retail spending will go toward automated customer service agents and expert shopping advisors & product recommendation systems. The banking industry will focus its investments on automated threat intelligence and prevention systems and fraud analysis and investigation. Other industries that will make significant investments in AI systems throughout the forecast include discrete manufacturing, process manufacturing, healthcare, and professional services. The fastest spending growth will come from the media industry and federal/central governments with five-year CAGRs of 33.7% and 33.6% respectively.”

Marianne D’Aquila, IDC research manager in the Customer Insights & Analysis department said, “”Artificial Intelligence (AI) has moved well beyond prototyping and into the phase of execution and implementation.” She also remarked, “Strategic decision makers across all industries are now grappling with the question of how to effectively proceed with their AI journey. Some have been more successful than others, as evidenced by banking, retail, manufacturing, healthcare, and professional services firms making up more than half of the AI spend. Despite the learning curve, IDC sees higher than average five-year annual compounded growth in government, media, telecommunications, and personal and consumer services.”

The biggest AI use cases

The three largest use cases for AI currently are: automated customer service agents, automated threat intelligence and prevention systems, and sales process recommendation and automation. But in the future, the use cases that will see the fastest spending growth over the 2018-2023 forecast period are automated human resources (43.3% CAGR) and pharmaceutical research and development (36.7% CAGR). However, eight other use cases will have spending growth with five-year CAGRs greater than 30%.

Where is AI investment happening?

According to IDC, the United States will deliver more than 50% of all AI spending throughout the forecast, led by the retail and banking industries. In second place is Western Europe where banking and discrete manufacturing will show the biggest demand. China will be the third largest region for AI spending with retail, state/local government, and professional services being the leading users, and Japan is another country to watch as its AI use is predicted to have a 45.3% CAGR growth in spending on AI up to 2023.

AI Speeds up Drug Design as World Searches for Covid-19 Cure

On By mehranmuslimiblogIn AI2 Comments

The use of Artificial Intelligence (AI) is surging, and one area in which its use is even more important in 2020 – The Year of a Global Pandemic –, is in health technology, or healthtech.

Berlin-based, non-profit think tank dGen has just released a new report, “AI, Privacy, and Genomics: The Next Era of Drug Design”, which looks at the issue of privacy and access to genetic data for companies using AI to speed up and improve drug design.

With articles about work on a vaccine for Covid-19 flooding newspapers every day, most people are now more aware of the typical timelines involved in creating new drugs. They certainly don’t appear overnight: as the dGen report states, “the average drug today takes 10-12 years and cost $2 billion.” However, the arrival of the new coronavirus has forced researchers to think more in terms of 12-18 months, which is like exchanging a leisurely world cruise for supersonic flight.

Enter AI, which in 2020 is only just entering drug R&D where it is being used to test and improve candidate drugs before they can be fully accredited by regulators, such as the FDA in the USA.

But there is one area of concern: genetic information is central to many AI-enabled drug discovery startups. To expand this innovation, a number of issues with using genetic data must be resolved. The dGen report lists these as:

  • ownership
  • secure storage
  • availability to multiple research parties.

In order for all of us to accept the wider use of AI in drug design, privacy concerns must be addressed using the privacy-preserving techniques in Machine Learning. These allow researchers to process genetic material without fully revealing its source.

While this is crucial for privacy, the techniques do not address the issue of ownership, or ways to audit the system. What the dGen report proposes is a decentralised pan-European biobank network that makes information available to researchers, but all access requests have to be logged. In that way, we all know who has looked at our genetic data. Furthermore, it would allow us as individuals to grant or deny these requests and track the use of our information.

dGen’s Top Predictions for 2030

Based on better privacy-preserving technologies and an access network, dGen’s top predictions for 2030 are:

  • Better collaboration networks will emerge.
  • Genetic privacy laws will be overhauled.
  • AI will become a fundamental part of drug discovery.
  • Pharmaceutical giants won’t be toppled, but they won’t get out unscathed as biotech startups take the field.

The views of industry leaders

It is also interesting to note the responses to the dGen report from those working in AI and healthtech. The think tank interviewed industry leaders from Aidence, Gero, Alphanosos, e-Estonia, Qunatlib and Turbine amongst others.

Maxim Kholin, Gero Co-Founder said,‘We believe that AI can accelerate the drug discovery process by proper understanding of human diseases from large biomedical data. The data-driven approach should help establish the genetic determinants and molecular markers of the disease’. While, Pascal Mayer, Founder of Alphanosos, which is specialised in plant-based pharamaceuticals, told dGen: ‘While currently working really well on bacteria, we are confident AI-enabled plant-based drug discovery shall be successful in fighting viruses as well’.

This work is important for all of us who have an interest in how emerging technology can contribute to a decentralised future in Europe and what this might mean for people, society, private entities, and the public sector over the coming decades. It is, of course, of a signifiant interest to us all right now, as the search for a Covid-19 cure continues.

For a copy of the Full Report contact:

Francisco Rodríguez

francisco@dgen.org

Technology will drive this decade

On By mehranmuslimiblogIn AI, Big Data, Blockchain, InnovationLeave a comment

This year the global pandemic has forced most of the world to rely more on technology. With more people working from home — something that is almost certain to become the new normal for those who can perform their job remotely –plus the need for more apps to assist with work and in monitoring public health, there has surely never been a bigger opportunity for the tech sector.

Bernard Marr in Forbes has identified 25 ways in which technology will define this decade, including an area I am particularly interested in, which is Artificial Intelligence. This he believes, and I agree, will be a driving force behind many of the other tech solutions.

AI will be central to the development of the Internet of Things, which is the ever-growing number of “smart” devices and objects that are connected to the Internet. We will also see a boom in ‘wearables’ that will go way beyond the current fitness trackers. There will be an industry dedicated to “wearable technology designed to improve human performance and help us live healthier, safer, more efficient lives.”

Big Data refers is another feature of the next ten years. It refers to the massive amount of data created worldwide and we’ll see advance augmented analytics emerge to deal with it, supported by AI.

Blockchain is another important tool that could revolutionise many parts of business, particularly as it facilitates trusted transactions, as Marr says.

For those of you who are of a sci-fi frame of mind, there will be “digitally extended realities. These will include virtual reality, augmented reality, and mixed reality, all aimed at enhancing the virtual experience.

The concept of “digital twins” is also pretty futuristic. Marr explains: “A digital twin is a digital copy of an actual physical object, product, process, or ecosystem. This innovative technology allows us to try out alterations and adjustments that would be too expensive or risky to try out on the real physical object.” The potential applications are numerous, from the arts to science and more.

I’m sure you’ve guessed that there will be more Alexas and Siris, with chatbots being our first point of customer service for many brands, and facial recognition will grow, although the regulations about its use do need to be ironed out.

Many of us are also waiting for the quantum computers to be unleashed, and that could happen before 2030.

You can read about all the other opportunities at Marr’s Forbes article (linked above), or in his book, Tech Trends in Practice: The 25 Technologies That Are Driving The 4th Industrial Revolution.

Prepare yourself for what’s coming!

Siri is witty, but knows her limits!

On By mehranmuslimiblogIn AI, Fintech, TechLeave a comment

Related image

Back in 1956, a man called John McCarthy coined the term AI for artificial intelligence. However it is only in recent years that we have personally witnessed the benefits of AI, and its mass scale adoption by larger enterprises. One of the things that has encouraged the use of AI is the need to understand data patterns, because companies want to know much more about their target audience and Ai allows them to gain useful insights into consumer behaviour.

There is much to be gained by understanding AI, including the fact that it is segmented into ‘weak’ and ‘strong’ sectors.

WEAK AI
Weak AI is also known as Narrow AI. This covers systems set up to accomplish simple tasks or solve specific problems. Weak AI works according to the rules that are set and is bound by it. However, just because it is labelled ‘weak’ doesn’t mean it is inferior: it is extremely good at the tasks it is made for. Siri is an example of ‘Weak AI. Siri is able t hold conversations, sometimes even quite witty ones, but essentially it operates in a predefined manner. And you can experience its ‘narrowness’ when you try to make it perform a task it is not programmed to do.

Company chatbots are similar. They respond appropriately when customers ask questions, and they are accurate. The AI is even capable of managing situations that are extremely complex, but the intelligence level is restricted to providing solutions to problems that are already programmed into the system.
STRONG AI
As you can imagine, ‘Strong AI’ has much more potential, because it is set up to try to mimic the human brain.  It is so powerful that the actions performed by the system are exactly similar to the actions and decisions of a human being. It also has the understanding power and consciousness.

However, the difficulty lies in defining intelligence accurately. It is almost impossible or highly difficult to determine success or set boundaries to intelligence as far as strong AI is concerned. And that is why people still prefer the ‘weak’ version, because it does not fully encompass intelligence, instead it focuses on completing a particular task it is assigned to complete. As a result it has become tremendously popular in the finance industry.
Finance and AI
The finance industry has benefited more than many by the introduction of AI. It is used in risk assessment, fraud detection, giving financial advice, investment trading, and finance management.

Artificial Intelligence can be used in processes that involve auditing financial transactions, and it can analyse complicated tax changes.

In the future, we may find companies basing business decisions on AI, as well as forecasting consumer behaviour and adapting a business to those changes at a much faster pace.

Artificial Intelligence is going to help people and businesses make smarter decisions, but as always we need to remain mindlful of finding the right balance between humans and machines.