Knowledge graph (KG) embeddings have been a mainstream approach for reasoning over incomplete KGs. However, limited by their inherently shallow and static architectures, they can hardly deal with the rising focus on complex logical queries, which comprise logical operators, imputed edges, multiple source entities, and unknown intermediate entities. In this work, we present the Knowledge Graph Transformer (kgTransformer) with masked pre-training and fine-tuning strategies. We design a KG triple transformation method to enable Transformer to handle KGs, which is further strengthened by the Mixture-of-Experts (MoE) sparse activation. We then formulate the complex logical queries as masked prediction and introduce a two-stage masked pre-training strategy to improve transferability and generalizability. Extensive experiments on two benchmarks demonstrate that kgTransformer can consistently outperform both KG embedding-based baselines and advanced encoders on nine in-domain and out-of-domain reasoning tasks. Additionally, kgTransformer can reason with explainability via providing the full reasoning paths to interpret given answers.

SAN ANTONIO, Aug. 15, 2022 /CNW/ -- Artificial intelligence (AI) will create new revenue and growth opportunities for start-ups and global information and communication technology (ICT) companies, finds Frost & Sullivan's recent analysis, Global Artificial Intelligence (AI) Market. The adoption of AI technologies across industries unleashes innovative business models, drives operational efficiencies, and creates strategic differentiation. Additionally, the pace of digital transformation and AI adoption has accelerated as organizations explore new means of creating sustainable business models and driving customer value. "The move to large-scale AI adoption requires a holistic AI strategy coupled with an ethical and responsible framework to ensure sustainable and long-term adoption," said, ICT Industry Analyst at Frost & Sullivan. "Going forward, deploying AI technologies and operationalizing an ethical AI framework within an organization and throughout the AI development and management life cycle will require a well-defined approach and business as well as the alignment of all technology stakeholders."

The recent influx and growth of machine learning and artificial intelligence rises questions about the way in which creative processes evolve.

The researcher is expected to have (i) a strong background in machine learning, and (ii) motivation to pursue multidisciplinary research at the …

AMIS African Master's Degree in Machine Intelligence provides brilliant young Africans with state-of-the-art training in machine learning.

Artificial intelligence is spreading into health care, often as software or a computer program capable of learning from large amounts of data and making predictions to guide care or help patients. Investors see health care's future as inextricably linked with artificial intelligence. That's obvious from the cash pouring into AI-enabled digital health startups, including more than $3 billion in the first half of 2022 alone and nearly $10 billion in 2021, according to a Rock Health investment analysis commissioned by POLITICO. And no wonder, considering the bold predictions technologists have made. At a conference in 2016, Geoffrey Hinton, British cognitive psychologist and "godfather" of AI, said radiologists would soon go the way of typesetters and bank tellers: "People should stop training radiologists now. It's just completely obvious that, within five years, deep learning is going to do better."

I distinctly remember the moment I was first intrigued by the possibilities of AI Art. On December 13th, 2021 I was scrolling through Twitter and breaking up the endless parade of apocalyptic news stories, vicious wisecracks and obscure movie trivia fighting for space on my feed was a puzzling and bizarre comic-grotesquerie "Elon Musk Dying in Space," created by one @wagface. No malice towards Mr. Musk, but one thing I love about Twitter is how the rich and poor, the powerful and anonymous are all trapped together in the same canvas sack, and this was a striking example of an anonymous online wise-guy turning the tools of cutting edge technology against one of the world's most pre-eminent technologists. I was also totally baffled, "What, exactly, am I looking at?" The image's melted plastic, smeared pixel future-primitive aesthetic couldn't've been more appropriate towards the subject at hand, but how was this nightmare created and what else is it capable of creating?

Artificial Intelligence is currently not on Netflix. Movies and series tend to come and go quite a lot in the streaming service unless they're Netflix …

The script starts simply enough: A couple is at the end of dinner. Conversation winds down, the wine is almost finished. After a silence, the man says he wants to play a game. UsingGPT-3, we developed a short film script called Date Night. Tired of off-kilter AI like Cleverbot, we wanted to use more robust tech in our work.

I should like the 1973 film Soylent Green. Actually, I should love it. The movie deals with issues that are even more important now than they were 50 years ago. And as someone who's spent plenty of time exploring the connections between sci-fi films, technology innovation, and the future, I feel a certain professional obligation to sing its praises. Instead, though, I find myself frustrated by the movie and its hyperbolic and naive handling of complex themes.