Matt Wood

Check out this new SIGMOD '24 scientific paper. Our customers love Amazon MemoryDB for its low latency performance, rich flexible API, large scale (up to 500 nodes per cluster), security, availability (4 9s SLA), and AWS's operational excellence. We designed MemoryDB for 11 9s of durability while still providing in-memory performance. My team created a nice technical scientific paper on MemoryDB's architecture. If you would like to learn about what's under the hood, check out this SIGMOD '24 paper. Yacine Taleb, Xingbo Wang, Nan Yan, Allen Samuels, Kevin McGehee, Stefan Mueller, and Jean G. - excellent work publishing this paper! https://lnkd.in/gFXPvci8 #aws #memorydb #inmemory #databases #durability #science #sigmod

192

6 Comments

Google Cloud Storage customers are increasingly running workloads like analytics and AI/ML which expect filesystem-like semantics and structure. We are excited to announce the preview release of Hierarchical Namespace for Cloud Storage, a new bucket creation option that organizes your bucket to look and act more like a filesystem. This provides better performance, consistency, and manageability for file-oriented workloads on object storage. We would love for you to try it out and give us your feedback! https://lnkd.in/g59_Q_N8

74

2 Comments

Machine learning governance plays an important role for organizations of all sizes to successfully scale their ML usage across a variety of use cases and also mitigate their technical and operational risks. To make this experience easier for our customers, AWS recently released a new Amazon SageMaker and Amazon DataZone integration that will streamline ML governance. https://lnkd.in/eD7FQyh5 This integration allows organizations of all sizes to ✅ Discover and access requests from Amazon DataZone directly within SageMaker ✅ Help unify infrastructure controls and permissions ✅ Streamline end-to-end ML workflows from data preparation to model deployment

574

4 Comments

Google's Workload Optimized Infrastructure at Next '24 Discover how Google Cloud is advancing workload-optimized infrastructure with innovations like Axion CPU & AI Hypercomputer, storage, & more. https://lnkd.in/g9AXr9CH #GoogleCloudNext

1

ONNX is an open source machine learning (ML) framework that provides interoperability across a wide range of frameworks, operating systems, and hardware platforms. This new blog post shows you how to run ONNX Runtime inference on #AWS Graviton3 and how to configure to use optimized GEMM kernels. With these optimizations, you can see up to 65% better performance for fp32 inference and up to 30% better performance for int8 quantized inference for several natural language processing (NLP) models on Graviton3: https://lnkd.in/giWYk6Hq

116

4 Comments

Exciting news! From the White House: "Microsoft will invest $3.3 billion in a new datacenter. Microsoft is committed to creating good-paying jobs with growth pathways and comprehensive benefits such as paid family leave. Microsoft will pair its datacenter investment with a commitment to investing in innovation and workforce in Racine and statewide. Microsoft will partner with Gateway Technical College to develop a Datacenter Academy that trains 1,000 Wisconsinites for datacenter and STEM roles by 2030, and will employ up to 2,000 people in permanent roles at its Racine facility. And, Microsoft will build a Co-Innovation Lab in southeast Wisconsin, as well as team up with the startup accelerator Gener8tor to train 1,000 business leaders to adopt AI in their operations, so that Wisconsin manufacturers can seize AI’s promise. Together, these investments will position the industrial heartland to lead the way in industries of the future."

88

2 Comments

How to do iterative development for ML with Dockers on Amazon SageMaker Studio

9

1 Comment

I love how Satya says “At the end of the day, companies will have to take a process, simplify the process, automate the process, and apply these solutions,” Nadella said. “And so, that requires not just technology, but in fact, companies to go do the hard work of culturally changing how they adopt technology.” “We’re also taking our own medicine to apply this across every process,” he added. Remember, AI is a cultural shift, not just a technological one. Start small and show value, then scale up. Pick smaller use cases and show immediate value. Spend some time experimenting with those use cases. Once you find a pattern that works, you can start implementing it at scale. Also, talk to a partner who has experience with AI implementation. Check out the article linked below for more insights from Satya Nadella on the importance of AI culture. Thanks, Mike Reinhart, for the article. #ai #copilot #quisitive

29

1 Comment

More details about the mighty phi-3 family of SLMs. Such a key development as GenAI Dev becomes more about always optimizing and orchestrating with LLMs routing to LLMs and SLMs continuously to balance complexity, latency, cost and more! https://lnkd.in/gGQYqNKt

9

What makes success stories like Observe.AI so exciting for me is witnessing MongoDB's evolution into an AI-accelerating data platform. For an AI-centric company like Observe.AI, choosing the right data architecture was the star. And they recognised MongoDB's distinct strengths to flex across databases, analytics, search, mobile data management and now vector databases for generative AI workloads. Our powerful indexing and querying capabilities allow Observe.AI's data scientists to quickly access and analyse the data powering their AI models. Read the blog to know how MongoDB is a core enabler of their innovative AI stack. #MongoDB #artificialintelligence #dataanalytics

28

Typically most #llm work we do is to reduce the responses down to JSON, but LLms even #llama3 do well with structured data as SQL. I’ve built entire schemas fairly rapidly in the early days of #genai

4

My latest blog post details how to set up your local Windows computer to fine-tune Llama3 and similar models. #generativeai #llm #windows #artificialintelligence

5

Databricks gets a top score💪of 3.38 for its DBRX AI model for language, a big win for CEO Ali Ghodsi and President Andy Kofoid. DBRX Score: 3.38 / Strategy Score: 4.34 / Market Presence: 3 “Databricks’ offering is a good choice for enterprise customers who want a capable model that includes enterprise tooling to not only build solutions and fine-tune models, but also to pretrain their own model with their own data,” #Forrester said. See how Databricks stacks up against OpenAI, AWS & the other Top 10 AI FMs for language in the world: #DataAIsummit #databricks #AI #aifoundationmodels #genai

3

Teragonia operates at the bleeding edge of leveraging AI to accelerate enterprise value growth for private equity backed companies. Here’s the first of our “What’s new in AI” series. More exciting updates to come in the coming weeks, stay tuned! #Teragonia #ValueCreation #AnalyticsEngineering #PrivateEquity #PEBacked #PortfolioCompany #GenAI #GenerativeAI #Innovation #ArtificialIntelligence #DataScience #FinancialSponsor #MachineLearning #BusinessIntelligence #360CustomerJourney #DataModel #ScalableSystems #ArtificialIntelligence #GlobalData #IntellectualHumility #mergers #acquisitions #divestitures #investmentbanking #mergersandacquisitions #restructuring #capitalmarkets #dataintegration #dataanalytics #analytics #datawarehouse #datawarehousing #sellside #exitpreparation #exitplanning

31

1 Comment

The emergence of enterprise AI products interweaving with operational workflows is an exciting development. It will be fascinating to see how this integration generates value for customers. https://lnkd.in/dcfYgzrf

11

With fine-tuning functionality for its Command R #LLMs, Cohere helps customers (like Oracle) realize high performance #ai processing at lower costs. Kieron Allen puts the new functionality in context in his analysis on Acceleration Economy: https://lnkd.in/eGwJvWCK

4

If you'll be at the #DataAISummit, join Ashok Singamaneni and myself (Scott Haines) as we teach you the ropes of building "Effective Lakehouse Streaming with Delta Lake and Friends". https://lnkd.in/gqmcJmRC We'll be teaching lessons learned (the hard way), and showing how streaming-first is the correct fit for "most" if not all your workflows. Learn to leverage #DeltaLake like an expert, and we'll introduce you to some effortless patterns for making your streaming journey a breeze. You'll also hear from Ashok Singamaneni as we talk about how to leverage painless workflow orchestration with #brickflow, and how to build data trust-networks using #sparkexpectations. #spark #deltalake #sparkexpectations #brickflow #nike #oss #dataai

92

11 Comments

Alphabet (GOOGL) results are in for Q1 2024, Google Cloud brought in $9.57 billion. Google Cloud continues to grow at a rapid pace, increasing revenue by ~28% YoY. Google Cloud continues to be profitable. Google Cloud’s Q1 2024 revenue of $9.57 billion represents ~12% of Alphabet’s total revenue of $80.53 billion. Google Cloud sees surging AI momentum, solidifying its position as the leading AI cloud services provider. Full results can be found here: https://lnkd.in/edYKnSUK #GoogleCloud #Google #Alphabet #Cloud #AI #GenAI

36