Tag: machine learning
TigerGraph Unveils ML Workbench, Winners of Its ‘Graph For All Million Dollar Challenge’
Graph analytics platform TigerGraph has just released its new TigerGraph ML Workbench, a Jupyter-based Python development framework. TigerGraph says this machine learning toolkit “enables data scientists to signific Read more…
Galileo Emerges from Stealth with Collaborative MLOps Platform
There’s a new player in the hot MLOps market: Galileo. Founded by Google and Uber AI alumni, the company emerged from stealth this week with $5.1 million in seed funding. Galileo is an intelligence platform for unst Read more…
Payment Fraud at Record Lows Thanks to Analytics and AI, Visa Says
Despite a massive increase in online activity during the COVID-19 pandemic, fraud on the Visa payment network is at an all time low, the company says. One of the chief reasons for that success is a big investment in adva Read more…
Unstructured Data Vs. Environment Reflected in Earth Day Commitments
Today is Earth Day, which means millions of people are taking time to think about how their actions are impacting the planet. The reflections are especially important for those in the IT business, where every byte of dat Read more…
Fighting Harmful Bias in AI/ML with a Lifelong Approach to Ethics Training
Today, artificial intelligence and machine learning technologies influence and even make some of our decisions, from which shows we stream to who is granted parole. While these are sophisticated use cases, they represent Read more…
Stemming vs Lemmatization in NLP
Stemming has long been accepted as an important part of natural language processing (NLP). However, as both artificial intelligence (AI) and NLP have evolved over the years, expectations of the accuracy of what constitut Read more…
Birds Aren’t Real. And Neither Is MLOps
Are birds real? A group of 20-somethings tried to convince us they weren’t in the past few years, to varying degrees of success. And now a University of Washington professor wants us to believe that MLOps isn’t real, Read more…
Pinecone to Bolster Vector Search Engineering Team Following Series A
Pinecone Systems, a pioneer in enabling vector search, will be bolstering its engineering team to solidify its early momentum in the booming vector database business following its $28 million Series A, the company told D Read more…
Oracle Announces New ML Capabilities for MySQL HeatWave
Today, Oracle announced its MySQL HeatWave database service now supports in-database machine learning as an additional capability to the service’s existing transaction processing and analytics. HeatWave ML is complimen Read more…
Computer Vision Platform Datagen Raises $50M Series B
Datagen, a firm specializing in computer vision artificial intelligence, announced it has raised $50 million in a Series B round bringing its total financing to $70 million. Computer vision (CV) has quickly become ubi Read more…
Nvidia CEO Touts a ‘Million X’ Speedup in AI
A decade ago, Google talked about “thinking in 10x.” Whether it’s Moore’s Law or the current rate of inflation, Nvidia’s CEO Jensen Huang has one-upped his fellow Silicon Valley technologists by thinking in mil Read more…
Nvidia Bolsters Edge AI and Autonomous Robots at GTC 2022
Amid the flood of news coming out of Nvidia’s GPU Technology Conference (GTC) today were pair of announcements aimed at accelerating the development of AI on the edge and enabling autonomous mobile robots, or AMRs. Read more…
Five Ways ML Can Drive Enterprise-Wide Business Impact in the Era of Big Data
While machine learning has been around–and growing more mainstream–for decades, its popularity is exploding in the era of big data with the market expected to expand at a 42% compound annual growth rate by 2024. With Read more…
Databricks Launches Lakehouse for Healthcare and Life Sciences
Databricks has announced the launch of its new lakehouse platform, the Databricks Lakehouse for Healthcare and Life Sciences. According to the company's press release, Databricks Lakehouse for Healthcare and Life Scie Read more…
Optimizing Your AI/ML Efforts with Localization
There’s an old saying that applies well to artificial intelligence and the data that powers it: “Garbage in, garbage out.” Gartner found that only 47% of ML/AI models go from prototype to production. These models a Read more…
Observability and AIOps Tools Rise with Big MELT Data
The hottest space in big data at the moment arguably exists between the two pillars of AIOps and observability, where a crush of metric, event, log, and trace (MELT) data threatens to overwhelm IT professionals. Not surp Read more…
MIT-IBM Watson AI Lab Tackles Power Grid Failures with AI
Next time your power stays on during a severe weather event, you may have a machine learning model to thank. Researchers at the MIT-IBM Watson AI Lab are using artificial intelligence to solve power grid failures. The Read more…
Natural Language Processing: The Next Frontier in AI for the Enterprise
The power and practicality of artificial intelligence is largely undisputed. However, one of its longest-standing difficulties continues to be human language. A misspelled or misused word can frustratingly turn a chatbot Read more…
Five Ways to Shift to AI-First
According to Gartner, artificial intelligence will create $2.9 trillion of business value and 6.2 billion hours of worker productivity globally in 2022. Many companies are aiming for an AI-first strategy where machine Read more…
MLOps Pays Dividends for New York Life
Machine learning has the potential to generate millions of dollars in savings and revenue growth for organizations. Nobody in the data business doubts that anymore. But unless ML models are actually put into production, Read more…
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