All in artificial intelligence

Specialization and Modularity in AI Architecture with Multi-Agent Systems

Dean Mai
artificial intelligence, software

Unstructured data encompasses a wide array of information types that do not conform to predefined data models or organized in traditional relational databases. This includes text documents, emails, social media posts, images, audio files, videos, and sensor data. The inherent lack of structure makes this data difficult to process using conventional methods, yet it often contains valuable insights that can drive innovation, improve decision-making, and enhance customer experiences.

Adopting Function-as-a-Service (FaaS) for AI workflows

Dean Mai
artificial intelligence, software

Unstructured data encompasses a wide array of information types that do not conform to predefined data models or organized in traditional relational databases. This includes text documents, emails, social media posts, images, audio files, videos, and sensor data. The inherent lack of structure makes this data difficult to process using conventional methods, yet it often contains valuable insights that can drive innovation, improve decision-making, and enhance customer experiences.

Architectural Paradigms for Scalable Unstructured Data Processing in Enterprise

Dean Mai
artificial intelligence

Unstructured data encompasses a wide array of information types that do not conform to predefined data models or organized in traditional relational databases. This includes text documents, emails, social media posts, images, audio files, videos, and sensor data. The inherent lack of structure makes this data difficult to process using conventional methods, yet it often contains valuable insights that can drive innovation, improve decision-making, and enhance customer experiences.

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

Dean Mai
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.

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

Dean Mai
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.

Qualia and artificial neuron bridges

Dean Mai
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.

Swarm intelligence: from natural to artificial systems

Dean Mai
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.

Legal personhood for artificial intelligences

Dean Mai
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.

Cortical interface: ‘Conscious-competence’ model

Dean Mai
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.

Ambient intelligence: A new multidisciplinary paradigm

Dean Mai
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.