Hot Artificial Intelligence (AI) Technologies

Based on Forrester’s analysis, here’s my list of the 10 hottest AI technologies:

Natural Language Generation: Producing text from computer data. Currently used in customer service, report generation, and summarizing business intelligence insights. Sample vendors: Attivio, Cambridge Semantics, Digital Reasoning, Lucidworks, Narrative Science, SAS.

Speech Recognition: Transcribe and transform human speech into format useful for computer applications. Currently used in interactive voice response systems and mobile applications. Sample vendors: NICE, Nuance Communications, OpenText, Verint Systems.

Virtual Agents: “The current darling of the media,” says Forrester (I believe they refer to my evolving relationships with Alexa), from simple chatbots to advanced systems that can network with humans. Currently used in customer service and support and as a smart home manager. Sample vendors: Amazon, Apple, Artificial Solutions, Assist AI, Creative Virtual, Google, IBM, IPsoft, Microsoft, Satisfi.

Machine Learning Platforms: Providing algorithms, APIs, development and training toolkits, data, as well as computing power to design, train, and deploy models into applications, processes, and other machines. Currently used in a wide range of enterprise applications, mostly `involving prediction or classification. Sample vendors: Amazon, Fractal Analytics, Google,, Microsoft, SAS, Skytree.

AI-optimized Hardware: Graphics processing units (GPU) and appliances specifically designed and architected to efficiently run AI-oriented computational jobs. Currently primarily making a difference in deep learning applications. Sample vendors: Alluviate, Cray, Google, IBM, Intel, Nvidia.

Decision Management: Engines that insert rules and logic into AI systems and used for initial setup/training and ongoing maintenance and tuning. A mature technology, it is used in a wide variety of enterprise applications, assisting in or performing automated decision-making. Sample vendors: Advanced Systems Concepts, Informatica, Maana, Pegasystems, UiPath.

Deep Learning Platforms: A special type of machine learning consisting of artificial neural networks with multiple abstraction layers. Currently primarily used in pattern recognition and classification applications supported by very large data sets. Sample vendors: Deep Instinct, Ersatz Labs, Fluid AI, MathWorks, Peltarion, Saffron Technology, Sentient Technologies.

Biometrics: Enable more natural interactions between humans and machines, including but not limited to image and touch recognition, speech, and body language. Currently used primarily in market research. Sample vendors: 3VR, Affectiva, Agnitio, FaceFirst, Sensory, Synqera, Tahzoo.

Robotic Process Automation: Using scripts and other methods to automate human action to support efficient business processes. Currently used where it’s too expensive or inefficient for humans to execute a task or a process. Sample vendors: Advanced Systems Concepts, Automation Anywhere, Blue Prism, UiPath, WorkFusion.

Text Analytics and NLP: Natural language processing (NLP) uses and supports text analytics by facilitating the understanding of sentence structure and meaning, sentiment, and intent through statistical and machine learning methods. Currently used in fraud detection and security, a wide range of automated assistants, and applications for mining unstructured data. Sample vendors: Basis Technology, Coveo, Expert System, Indico, Knime, Lexalytics, Linguamatics, Mindbreeze, Sinequa, Stratifyd, Synapsify.

Digital Trust

Digitization is here to stay and we could either hide from it or
embrace it, but as you remember from the times of old, sooner or later
you would still be found.

The embracement means that our processes with
the assorted paper trail go digital. Here is the thing about
digitization that few understands: The paper trail disappears. What´s on
the computer is the truth as there is no proof otherwise anymore.

everyone is thinking of all new ways we could use IOT, move our life
into the devices and in general be more efficient in everything
involving information it is my task to make sure that you all could do
that and trust that the computer doesn’t say no.

The last number
of years we have seen a very large increase in attacks, not only
standard Trojan attacks but DDOS, attacks on IOT, attacks on industries,
power grids and attacks on our political systems using computerized
attacks. We have been trying to fend those of with traditional security
but to no avail. We are lagging behind. It is time to start working
differently with security and move far beyond the traditional setup.

testing, secure coding, and surveillance, to name a few, will still be
brick and mortar in the digital world but what we need is to implement
functions to guarantee the integrity of the information and systems. Not
only do we need to be sure that they are more or less non-hackable but
even more do we need to have extensive logging of transactions that are
built on non-repudiation, that are built on a guaranteed extensive
identity management governed by a trusted party, that contains a trust
in the full transaction, no matter the device or geographical placement
of said device.

This is called Digital Trust. The security
department will not be the ones providing only firewalls and secure
testing anymore but the one helping you guarantee the trust in the
systems, that provides all the help needed for your customers to feel
that they could trust your company, that not only secures the systems
but have the automated functionality to quickly identify and rectify an
integrity error before this is even noticed by the users. There will be
errors, there will always be errors, there will always be attacks, some
even successful, but it is the Digital Trust-department that should
manage this by implementing integrity in all solutions, not only
confidentiality and availability.

With digitization comes Digital Trust. Without Digital Trust digitization will fail.

BlockChain Use Case Dilemma

If you’re thinking about experimenting with blockchain and you are
unsure if you actually need the benefits of a distributed ledger or not,
chances are you probably don’t need it! I found this as a simple, great
starting reference to question the use case:

I have shared it in my Linkedin but sharing again.

Digital Transformation, King Maker?

The right side of disruption: why digital transformation is the new kingmaker

businesses these days, it seems, want to associate themselves with
‘digital transformation’. But what does it actually mean, and what are
its IT implications? –