What’s new in AI, Part 1: Generative AI with Dan Jeffries
On Stability AI and Stable Diffusion’s rise to prominence, open source, business models, AI, use cases, and how to use and fine-tune Stable Diffusion What’s new in AI? That may sound like a moot question for a domain that has been moving extremely fast and making the news on a daily basis for the last […]
Read More →Nvidia doubles down on AI language models and inference as a substrate for the Metaverse, in data centers, the cloud and at the edge
At Nvidia's GTC event today, CEO Jensen Huang made announcements the company claims have the potential to transform multi-trillion dollar industries. We cherry-pick from the announcements, focusing on the hardware and software infrastructure that powers the applications that make the headlines.
Read More →Graph data standardization: It’s just a graph, making gravitational waves in the real world
AWS, Google, Neo4j, Oracle. These were just some of the vendors represented in the W3C workshop on web standardization for graph data, and what transcribed is bound to boost adoption of the hottest segment in data management: Graph.
Read More →Knowledge graphs, AI, and interoperability. The Year of the Graph Newsletter: February 2019
Knowledge graphs are spreading everywhere: from Airbnb and eBay to Alexa, and from using JSON-LD on the web for better SEO to leveraging taxonomy to define AI. Combining knowledge graphs and machine learning, benchmarking graph databases, and W3C initiative for interoperability shaping up. January 2019 has been a lively month in the graph landscape. Read […]
Read More →More graph databases. The Year of the Graph Newsletter Vol. 8, December 2018
Redis announces RedisGraph and a benchmark, TigerGraph goes AWS, AWS hands-on experiences, new features from Stardog and AnzoGraph, Graphs and Machine Learning, GraphQL, Atlas, DBpedia, Connected Data London and the Year of the Graph. I often get asked about graph databases – what they are, what are they good for, how to choose one, as […]
Read More →From big data to AI: Where are we now, and what is the road forward?
It took AI just a couple of years to go from undercurrent to mainstream. But despite rapid progress on many fronts, AI still is something few understand and fewer yet can master. Here are some pointers on how to make it work for you, regardless of where you are in your AI journey.
Read More →Graph gets funding. The Year of the Graph Newsletter Vol. 7, November 2018
October 2018 was the busiest month in the busiest year in graph history, hence the longest Year of the Graph newsletter to date. Neo4j lands a massive funding round, Tinkerpop is moving forward, the most important knowledge graph research event with key industry presence, W3C organizing a Workshop on Web Standardization for Graph Data, and […]
Read More →The past, present, and future of streaming: Flink, Spark, and the gang
Reactive, real-time applications require real-time, eventful data flows. This is the premise on which a number of streaming frameworks have proliferated. The latest milestone was adding ACID capabilities, so let us take stock of where we are in this journey down the stream — or river.
Read More →Controversy, thy name is Europe: Open credit scores, data-driven counter-forensics, and the regulation debate
Europe's biggest digital culture festival raises questions beyond the use of data.
Read More →The future of the future: Spark, big data insights, streaming and deep learning in the cloud
Apache Spark is hailed as being Hadoop's successor, claiming its throne as the hottest Big Data platform. What the founding fathers of Spark are saying and doing about its future and its positioning in the market has never been more timely.
Read More →