Dean Mai

I specialize in identifying disruptive, core technologies and strategic technology trends in early-stage startups, research universities, government sponsored laboratories and commercial companies.

In my current role, I lead sourcing of strategic technology investment opportunities and managing Dyson’s diligence and outreach processes, specifically in the U.S., Israel and China.

I write here (sporadically) on the convergence of science and engineering, with broader adopted interests in novel disruptive technologies, cognitive psychology, human-computer interaction (HCI), philosophy, linguistics and artificial intelligence (AI).

All in artificial intelligence

Jan 11
Jan 11 Edge computing and the Internet of Things: Investing in the future of autonomy

artificial intelligence

One of the most ubiquitous technological advancements making its way into devices we use every single day is autonomy. Autonomous technology via the use of artificial intelligence (AI) and machine learning (ML) algorithms enables core functions without human interference. As the adoption of ML becomes more widespread, more businesses are using ML models to support mission-critical operational processes. This increasing reliance on ML has created a need for real-time capabilities to improve accuracy and reliability, as well as reduce the feedback loop.

Jan 23
Jan 23 Federated machine learning as a distributed architecture for real-world implementations

artificial intelligence

Present performance of machine learning systems—optimization of parameters, weights, biases—at least in part relies on large volumes of training data which, as any other competitive asset, is dispersed, distributed, or maintained by various R&D and business data owners, rather than being stored by a single central entity. Collaboratively training a machine learning (ML) model on such distributed data—federated learning, or FL—can result in a more accurate and robust model than any participant could train in isolation.

Aug 9
Aug 9 Similar information rates across languages, regardless of varying speech rates

cognitive psychology, artificial intelligence

Language and linguistics are studied through a wide range of tools and perspectives. Over the past few years, a proliferation of mathematical methods, newly available datasets and computational modeling (namely probability and information theory) has led to an increased interest in information transmission efficiency across human languages.

Jun 24
Jun 24 Qualia and artificial neuron bridges

artificial intelligence

Is intelligence a prerequisite for experience, or only for expression of that experience? What if the occurrence of higher-order, self-reflexive states are not necessary and sufficient for consciousness? Although humans tend to believe that we perceive the true reality, the fact is that subjective image generated in our brains are far from being a truthful representation of real world. Nevertheless, generally our conscious experience of the world proves to be highly reliable and consistent in terms of mundane tasks.

Jan 2
Jan 2 Artificial neural networks and engineered interfaces

artificial intelligence, robotics

The need to express ourselves and communicate with others is fundamental to what it means to be human. Animal communication is typically non-syntactic, with signals which refer to whole situations. On the contrary, human language is syntactic, and signals consist of discrete components that have their own meaning. Human communication is enriched by the concomitant redundancy introduced by multimodal interaction. The vast expressive power of human language would be impossible without syntax, and the transition from non-syntactic to syntactic communication was an essential step in the evolution of human language. Syntax defines evolution.

Jul 19
Jul 19 Swarm intelligence: from natural to artificial systems

artificial intelligence

Complexity is natively intervened within data: if an operation is decomposable into rudimentary steps whose number varies depending on data complexity, exploiting a data sequence as a whole (collective effort of colony members in the specific task), rather than a single data input, can conduce to a much faster result. By forming a closed-loop system among large populations of independent agents, the ‘Swarm’, high-level intelligence can emerge that essentially exceeds the capacity of the individual participants. The intelligence of the universe is social.

Jun 15
Jun 15 Legal personhood for artificial intelligences

software, artificial intelligence, innovation

There are innumerable examples of other ways in which information technology has caused changes in the existing legislative structures. The law is naturally elastic, and can be expanded or amended to adapt to the new circumstances created by technological advancement. The continued development of artificial intelligence, however, may challenge the expansive character of the law because it presents an entirely novel situation. To begin with, artificial intelligence raises philosophical questions concerning the nature of the minds of human beings. These philosophical questions are connected to legal and ethical issues of creating machines that are programmed to possess the qualities that are innate and unique to human beings. If machines can be built to behave like humans, then they must be accorded some form of legal personality, similar to that which humans have. At the very least, the law must make provision for the changes that advanced artificial intelligence will cause in the society through the introduction of a new species capable of rational, logical thought. By deriving general guidelines based on the case law of the past, it should aid the lawmakers to close the gap on technological singularity.

Apr 23
Apr 23 Cortical interface: ‘Conscious-competence’ model

artificial intelligence

The unmitigated accuracy in inputting and outputting data through different medium interfaces (as well as our own technological fluency in using and utilizing information resources in itself) signals the multiplicity of subjectivities we easily form, participate in and are subjected to in our everyday lives. Humanity is on the path to significantly accelerate the evolution of intelligent life beyond its current human form and human limitations.

Mar 4
Mar 4 Understanding the theory of embodied cognition

artificial intelligence

Embodied cognition is a research theory that is generally all about the vast difference of having an active body and being situated in a structured environment adept to the kind of tasks that the brain has to perform in order to support adaptive task success. Herein the team if referred as the existence of a memory system that encodes data of agent’s motory and sensory competencies, stressing the importance of action for cognition, in such way that an agent is capable to tangibly interact with the physical world. The aspects of the agent's body beyond its brain play a significant causative and physically integral role in its cognitive processing. The only way to understand the mind, how it works, and subsequently train it is to consider the body and what helps the body and mind to function as one.

Nov 3
Nov 3 Ambient intelligence: A new multidisciplinary paradigm

artificial intelligence

The future of artificial intelligence is not so much about direct interaction between humans and machines, but rather indirect amalgamation with the technology that is all around us, as part of our everyday environment. Rather than having machines with all-purpose intelligence, humans will interact indirectly with machines having highly developed abilities in specific roles. Their sum will be a machine ecosystem that adapts to and aids in whatever humans are trying to do. In that future, the devices might feel more like parts of an overall environment we interact with, rather than separate units we use individually. This is what ambient intelligence is.