Gobekli Inc.

The key to humanizing technology is to make it more relatable, not more human.

Posted by Daniel Adiwardana, Senior Research Engineer, and Thang Luong, Senior Research Scientist, Google Research, Brain Team Modern co...

Facebook AI has made scientific progress in improving nuanced conversational skills, including consistency, specificity, and empathy.

How to avoid common pitfalls and unlock customer and business value

Academic publication about Unanimous AI and their work in the fields of Collective Intelligence, Artificial Intelligence and the SWARM software platform.

Swarm AI provides the interfaces and AI algorithms to enable “human swarms” to converge online, combining the knowledge, wisdom, insights, and intuitions of diverse groups into a single emergent intelligence.

The companies revealed upgrades for their phones that protect data and reduce reliance on the cloud. It also binds users more tightly to their ecosystems.

Blockchain has become very popular and suitable to the Internet of Things (IoT) field due to its nontamperability and decentralization properties. The number of IoT devices and leaders (who own IoT devices) is increased exponentially, and thus, data privacy and security are undoubtedly significant concerns. In this paper, we summarize some issues for the BeeKeeper system, a blockchain-based IoT system, proposed by Zhou et al., and then aim for presenting an improved solution for decentralized data aggregation (DDA) on IoT. Firstly, we formally state the security requirements of DDA. Secondly, we propose our basic DDA system by using secret sharing to improve its efficiency and smart contracts as the computing processors. Moreover, the proposed full-fledged system achieves data sharing (e.g., a leader to access data of others’ devices), which is realized by using local differential privacy and cryptographic primitives such as token-based encryption. Finally, to show the feasibility, we provide some implementations and experiments for the DDA systems.

Amit Sheth is a professor of computer science and engineering at the University of South Carolina.

DARPA project aims to use machine social intelligence to improve teamwork.

BetterUp Coaching, San Francisco, California. 852 likes · 597 talking about this · 26 were here. Our mission is to help people everywhere pursue their lives with greater clarity, purpose, and...

Licensing intellectual property allows the creators of IP the right to profit from their work by controlling who uses their creations and how they use them. The creator retains ownership rights during and after the license period.

Resources concerning the licensing of patent, trademark, copyright, and other intellectual property (IP), including technology protected by IP rights.

Artificial intelligence's (AI) presence continues to grow in many industries and within various technologies as innovative organizations use it for…

Bylined article by Technology Transactions partners Rebecca Eisner and Brad Peterson (both Chicago).

Many criticize gestural controls as being unintuitive and unnecessary. Despite this, widespread adoption is underway already, and the UI design world is burning the candle at both ends to develop solutions that are instinctively tactile. The challenges here are those of novelty. Even though gestural controls have been around since the early 1980s and have enjoyed a level of ubiquity since the early 2000s, designers are still in the beta-testing phase of making gestural controls intuitive for everyday use.

What gesture-based interactions reveal about a multimodal future

Lets talk about Graphical user interface(GUI). This is a form of user interface that for uses graphical icons and visual representations…

“Any sufficiently advanced technology is indistinguishable from magic.” -Arthur C Clarke

Artificial intelligence (AI)-powered technologies are becoming an integral part of youth's environments, impacting how they socialize and learn. Children (12 years of age and younger) often interact with AI through conversational agents (e.g., Siri and Alexa) that they speak with to receive information about the world. Conversational agents can mimic human social interactions, and it is important to develop socially intelligent agents appropriate for younger populations. Yet it is often unclear what data are curated to power many of these systems. This article applies a sociocultural developmental approach to examine child-centric intelligent conversational agents, including an overview of how children's development influences their social learning in the world and how that relates to AI. Examples are presented that reflect potential data types available for training AI models to generate children's conversational agents' speech. The ethical implications for building different datasets and training models using them are discussed as well as future directions for the use of social AI-driven technology for children.