Did you ever need data on a topic you wanted to research, and had a hard time finding it? Wish you could just Google it? Well, now you can do that.

Yes, Facebook is a data-driven monopoly. But the only real way to break it up is by getting hold of its data and functionality, one piece at a time. It will take a combination of tech, data, and social engineering to get there. And graphs -- personal knowledge graphs.

Being disrupted by Big Tech is one of the greatest concerns for any business. Good news: There may be a path to accelerate digital transformation and out-compete Big Tech, by leveraging domain knowledge.

You don't have to be a fortune teller to identify AI as the key trend for the 2020s. But there is nuance regarding AI hardware and software that deserves to be highlighted.

Data.world wants to eliminate data silos to answer business questions. Their bet to do this is to provide data catalogs powered by knowledge graphs and semantics. The choice of technology seems to hit the mark, but intangibles matter, too.

What exactly are knowledge graphs, and what's with all the hype about them? Learning to tell apart hype from reality, defining different types of graphs, and picking the right tools and database for your use case is essential if you want to be like the Airbnbs, Amazons, Googles, and LinkedIns of the world.

Siren promises the benefits of knowledge graphs, without the hassle of reinventing your existing data management and infrastructure

Knowledge graphs are among the most important technologies for the 2020s. Here is how they are evolving, with vendors and standard bodies listening, and platforms becoming fluent in many query languages

State of the art in analytics and AI can help address some of the most pressing issues in scientific research. Here is how top scientists are using them to facilitate coronavirus research.

A sui generis, multi-model open source database, designed from the ground up to be distributed. ArangoDB keeps up with the times and uses graph, and machine learning, as the entry points for its offering.

Data lakes can be a great asset, but they need an array of elements to work properly. We take a look at how it works for Montefiore Health System and discuss the role of semantics and graph databases in the data lake architecture.

Knowledge graphs are probably the best technology we have for data integration. But what about application integration? Knowledge graphs can help there, too, argues EnterpriseWeb.

Explainable AI in real life could mean Einstein not just answering your questions, but also providing justification. Advancing the state of the art in natural language processing is done on the intersection of graphs and machine learning.

A tour de force on progress in AI, by some of the world's leading experts and venture capitalists.

Gary Marcus, a prominent figure in AI, is on a mission to instill a breath of fresh air to a discipline he sees as in danger of stagnating. Knowledge graphs, the 20-year old hype, may have something to offer there.

In the new knowledge-based digital world, encoding and making use of business and operational knowledge is the key to making progress and staying competitive. Here's a shortlist of technologies and processes that can support this transition, and what they are about.

AI chips, MLOps, and ethics. Knowledge, and Graphs. COVID-19 as a mixed bag for technological progress and adoption

Graphs are everywhere. That has been the motto of graph aficionados for years, and now the world seems to be waking up to this.

Industry leaders discuss the "duct tape of data," if language models are a good way to approximate AI, and how to gain hybrid intelligence.

The butcher-on-the-bus is a rhetorical device that sheds light on human memory processes. Imagine recognising someone on a bus but struggling to place their… | 62 comments on LinkedIn

Graph databases are making a splash in the database market, with specialist, multimodal and cloud database suppliers jostling for a slice of the pie.

Irene Politkoff, Founder and Chief Product Evangelist at semantic modeling tools provider TopQuadrant, posted this description of the large language model (LLM) ChatGPT: “ChatGPT doesn’t access a database of facts to answer your questions. Instead, its responses are based on patterns that it saw in the training data. So ChatGPT is not always trustworthy.” Georgetown… Read More »Can we boost the confidence scores of LLM answers with the help of knowledge graphs?

Like many of you, I’ve been reading a lot lately about ChatGPT and LLMs, and how they will impact various aspects of our society. Some of…

Researchers develop a framework to capture the vast downstream impact and complex upstream dependencies that define the foundation model ecosystem.

Any database is pretty useless unless the user can ask, and get answers to, their questions.

In today's data-driven world, it is crucial to establish a clear boundary between your public and private data. Whilst banks, medical institutions, and spy… | 35 comments on LinkedIn

Co-authors: Sofus Macskássy, Carol Jin, Shiyong Lin, Xiaomin Wei, and Michael O’Neill

We present the Graph Forward-Forward (GFF) algorithm, an extension of the Forward-Forward procedure to graphs, able to handle features distributed over a graph's nodes. This allows training graph neural networks with forward passes only, without backpropagation. Our method is agnostic to the message-passing scheme, and provides a more biologically plausible learning scheme than backpropagation, while also carrying computational advantages. With GFF, graph neural networks are trained greedily layer by layer, using both positive and negative samples. We run experiments on 11 standard graph property prediction tasks, showing how GFF provides an effective alternative to backpropagation for training graph neural networks. This shows in particular that this procedure is remarkably efficient in spite of combining the per-layer training with the locality of the processing in a GNN.

AI-chatbot software for complex requirements

It can be hard to work out from Wikipedia if an Ontologist is a philosopher, a physicist or something completely different