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Databricks Introduces New Generative AI Tools, Investing in Lakehouse AI

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Databricks’ data-centric approach to AI makes it easier to build, deploy and manage large language model (LLM) applications, enabling customers to accelerate their generative AI journey
SAN FRANCISCO, June 28, 2023 /PRNewswire/ — At the sold-out Data + AI Summit, Databricks, the Data and AI company, today announced new Lakehouse AI innovations that allow customers to easily and efficiently develop generative AI applications, including large language models (LLMs), directly within the Databricks Lakehouse Platform. Lakehouse AI offers a unique, data-centric approach to AI, with built-in capabilities for the entire AI lifecycle and underlying monitoring and governance. New features that will help customers more easily implement generative AI use cases include: Vector Search, a curated collection of open source models, LLM-optimized Model Serving, MLflow 2.5 with LLM capabilities such as AI Gateway and Prompt Tools, and Lakehouse Monitoring.
The demand for generative AI is driving disruption across industries, creating urgency for technical teams to build generative AI models and LLMs on top of their own data to differentiate their offerings. However, data determines success with AI, and when the data platform is separate from the AI platform, it’s difficult to enforce and maintain clean, high-quality data. Additionally, the process of getting a model from experimentation to production, and the related tuning, operationalizing, and monitoring of the models, is complex and unreliable.
With Lakehouse AI, Databricks unifies the data and AI platform, so customers can develop their generative AI solutions faster and more successfully – from using foundational SaaS models to training their own custom models securely with their enterprise data. By bringing together data, AI models, LLM operations (LLMOps), monitoring and governance on the Databricks Lakehouse Platform, organizations can accelerate their generative AI journey.
“At JetBlue, we inspire humanity through our product, culture and customer service. We’ve embarked on an AI transformation over the past year because we believe AI, and in particular LLMs, can fuel increased productivity and better customer experience for our travelers,” said Sai Ravuru, Senior Manager of Data Science and Analytics at JetBlue. “Databricks has been instrumental in our AI and ML transformation and has helped us build our own LLM, enabling our team to more effectively use the BlueSky platform to make decisions using real-time streams of weather, aircraft sensors, FAA data feeds and more. The deployment is significantly improving our onboarding time for new users. We’re excited about all of Databricks’ data-centric AI innovations, enabling customers like us to build LLMs in the lakehouse and govern them from there.”
Offering the Best Data Platform to Develop Generative AI Solutions
Lakehouse AI unifies the AI lifecycle, from data collection and preparation, to model development and LLMOps, to serving and monitoring. Newly announced capabilities include:
Vector Search: Databricks Vector Search enables developers to improve the accuracy of their generative AI responses through embeddings search. It will fully manage and automatically create vector embeddings from files in Unity Catalog — Databricks’ flagship solution for unified search and governance across data, analytics and AI — and keep them updated automatically through seamless integrations Databricks Model Serving. Additionally, developers have the ability to add query filters to provide even better outcomes for their users.Fine-tuning in AutoML: Databricks AutoML now brings a low-code approach to fine-tuning LLMs. Customers can securely fine-tune LLMs using their own enterprise data and they will own the resulting model that’s produced by AutoML, without having to send data to a third party. Additionally, with MLflow, Unity Catalog and Model Serving integrations, the model can be easily shared within an organization, governed for appropriate use, served for inference in production and monitored.Curated open source models, backed by optimized Model Serving for high performance: Databricks has published a curated list of open source models available within Databricks Marketplace — including MPT-7B and Falcon-7B instruction-following and summarization models, and Stable Diffusion for image generation — making it easy to get started with generative AI across a variety of use cases. Lakehouse AI capabilities like Databricks Model Serving have been optimized for these models to ensure peak performance and cost optimization.Managing LLMOps Effectively and Reliably
Databricks also unveiled new innovations in LLMOps with the announcement of MLflow 2.5, the latest release of popular Linux Foundation open source project MLflow. This is Databricks’ latest contribution to one of the company’s flagship open source projects. MLflow is an open source platform for the machine learning lifecycle that sees nearly 11 million monthly downloads. MLflow 2.5 updates include:
MLflow AI Gateway: MLflow AI Gateway enables organizations to centrally manage credentials for SaaS models or model APIs and provide access-controlled routes for querying. Organizations can then provide these routes to various teams to integrate into their workflows or projects. Developers can easily swap out the backend model at any time to improve cost and quality, and switch across LLM providers. MLflow AI Gateway will also enable prediction caching to track repeated prompts and rate limiting to manage costs.MLflow Prompt Tools: New, no-code visual tools allow users to compare various models’ output based on a set of prompts, which are automatically tracked within MLflow. With integration into Databricks Model Serving, customers can deploy the relevant model to production.Additionally, following its release earlier this year, Databricks Model Serving has been optimized for the inference of LLMs up to 10x lower latency time and reduced costs. Fully managed by Databricks to offer frictionless infrastructure management, Model Serving now enables GPU-based inference support. It auto-logs and monitors all requests and responses to Delta Tables and ensures end-to-end lineage tracking through Unity Catalog. Finally, Model Serving quickly scales up from zero and back down as demand changes, reducing operational costs and ensuring customers pay only for the compute they use.
Intelligent Monitoring Across Data and AI Assets
Databricks also expanded its data and AI monitoring capabilities with the introduction of Databricks Lakehouse Monitoring to better monitor and manage all data and AI assets within the Lakehouse. Databricks Lakehouse Monitoring provides end-to-end visibility into data pipelines, to continuously monitor, tune and improve performance, without additional tools and complexity. By taking advantage of Unity Catalog, Lakehouse Monitoring provides users with deep insight into the lineage of their data and AI assets to ensure high quality, accuracy and reliability. Proactive detection and reporting will make it easy to spot and diagnose errors in pipelines, automatically perform root cause analysis and quickly find recommended solutions across the data lifecycle.
“We’ve reached an inflection point for organizations: leveraging AI is no longer aspirational — it is imperative for organizations to remain competitive,” said Ali Ghodsi, Co-Founder and CEO at Databricks. “Databricks has been on a mission to democratize data and AI for more than a decade and we’re continuing to innovate as we make the lakehouse the best place for building, owning and securing generative AI models.”
Databricks continues to expand the Lakehouse Platform, recently announcing Lakehouse Apps and the general availability of Databricks Marketplace, LakehouseIQ, new governance capabilities, and Delta Lake 3.0.
AvailabilityMLflow 2.5 features will be available in the July release of MLflow. New Databricks capabilities including Vector Search and Lakehouse Monitoring are currently in preview.
To learn more about Lakehouse AI watch the Data + AI Summit live: https://www.databricks.com/dataaisummit/watch
About DatabricksDatabricks is the Data and AI company. More than 10,000 organizations worldwide — including Comcast, Condé Nast, and over 50% of the Fortune 500 — rely on the Databricks Lakehouse Platform to unify their data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe. Founded by the original creators of Delta Lake, Apache Spark™, and MLflow, Databricks is on a mission to help data teams solve the world’s toughest problems. To learn more, follow Databricks on Twitter, LinkedIn, and Facebook.
Contact: [email protected] 
Safe Harbor Statement This information is provided to outline Databricks’ general product direction and is for informational purposes only. Customers who purchase Databricks services should make their purchase decisions relying solely upon services, features, and functions that are currently available. Unreleased features or functionality described in forward-looking statements are subject to change at Databricks discretion and may not be delivered as planned or at all.
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US Air Force Awards ThroughPut.ai Direct-to-Phase-II Contract for Boeing, Lockheed Martin, and Sikorsky Mission Design Series to Accelerate Aircraft Readiness

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Leveraging Data to Drive Maintenance-first actions that improve overall supply chain throughput across the DAF.
NEW YORK, May 28, 2024 /PRNewswire/ — ThroughPut.ai, the Supply Chain Decision Intelligence Pioneer, announces it has been selected by AFWERX for a (SBIR Direct-to-Phase II contract) in the amount of $1,248,627.00 focused on “AI-Powered Proactive Supply Chain Capabilities” to address the most pressing challenges in the Department of the Air Force (DAF). The Air Force Research Laboratory and AFWERX have partnered to streamline the Small Business Innovation Research (SBIR) and Small Business Technology Transfer (STTR) process by accelerating the small business experience through faster proposal to award timelines, changing the pool of potential applicants by expanding opportunities to small business and eliminating bureaucratic overhead by continually implementing process improvement changes in contract execution. The DAF began offering the Open Topic SBIR/STTR program in 2018 which expanded the range of innovations the DAF funded and now on April 17th, 2024, ThroughPut.ai will start its journey to create and provide innovative capabilities that will strengthen the national defense of the United States of America.

“ThroughPut.ai looks forward to supporting efforts to accelerate inventory flow across the United States Air Force,” said Ali Raza, CEO & Founder of ThroughPut.ai. “By driving inventory/materiel management changes at the maintenance endpoint first, supply chain improvements can then be amplified across the greater industrial base to create aircraft capacity.”
“The views expressed are those of the author and do not necessarily reflect the official policy or position of the Department of the Air Force, the Department of Defense, or the U.S. government.”
About (ThroughPut.ai)
ThroughPut.ai is a Silicon Valley-based supply chain optimization & predictive replenishment company. The company’s software AI platform has the ability to identify location-, product-, and customer-based demand changes sooner in order to adjust order frequencies, vendor sources, and parts buffer levels at a global and local scale. ThroughPut’s platform was designed by Fortune 500 & technology executives with real-world experience managing demand & supply chain disruptions and war-zone logistics across the Middle East.
About AFRLThe Air Force Research Laboratory is the primary scientific research and development center for the Department of the Air Force. AFRL plays an integral role in leading the discovery, development, and integration of affordable warfighting technologies for our air, space and cyberspace force. With a workforce of more than 12,500 across nine technology areas and 40 other operations across the globe, AFRL provides a diverse portfolio of science and technology ranging from fundamental to advanced research and technology development. For more information, visit afresearchlab.com.
About AFWERXAs the innovation arm of the DAF and a directorate within the Air Force Research Laboratory, AFWERX brings cutting-edge American ingenuity from small businesses and start-ups to address the most pressing challenges of the DAF. AFWERX employs approximately 370 military, civilian and contractor personnel at five hubs and sites executing an annual $1.4 billion budget. Since 2019, AFWERX has executed over 6,100 new contracts worth more than $4 billion to strengthen the U.S. defense industrial base and drive faster technology transition to operational capability. For more information, visit: www.afwerx.com. 
Company Press Contact:Ali RazaCEO/[email protected] 

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Data Center Investments Soar: 200% Rise Since 2016 and Projected 89% Increase by 2028

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USA News Group CommentaryIssued on behalf of Avant Technologies Inc.
VANCOUVER, BC, May 28, 2024 /PRNewswire/ — Since 2016, investment in data centre infrastructure has risen 200%, with a further 89% increase expected by 2028 as more opportunities emerge with the rise of artificial intelligence (AI). According to Jones Lang LaSalle Inc.’s CEO Christian Ulbrich, data centers are “the hottest asset class at the moment.” Analysts at Technavio are projecting the global data center market to record an additional US$329.82 billion in growth at a CAGR of 12.73% through 2027. Capitalizing on the opportunity are several players recently announcing developments regarding their involvement in the data centers sector, including

Avant Technologies Inc. (OTCQB: AVAI), Amazon.com, Inc. (NASDAQ: AMZN), Applied Digital Corporation (NASDAQ: APLD), Digital Realty Trust, Inc. (NYSE: DLR), and Equinix, Inc. (NASDAQ: EQIX).
As an early pioneer in generative AI, Avant Technologies Inc. (OTCQB: AVAI) continues to enhance its flagship asset, Avant AITM, a sophisticated machine and deep learning AI system designed for versatility and customization across various industries and applications. Recently, Avant announced plans to equip its AI-managed data center, currently in development, with High-Performance Computing (HPC) systems. According to IBM, HPC technology utilizes clusters of powerful processors working in parallel to process massive multi-dimensional data sets and solve complex problems at exceptionally high speeds.
“The rise of AI is revolutionizing industries, and Avant Technologies is committed to being at the forefront of this transformation,” said William Hisey, CEO of Avant. “By building an AI-managed data center with HPC systems, we will gain the computational power and infrastructure required to train and deploy sophisticated AI models, which will ultimately provide even greater value to our customers.”
The new data center will leverage AI-driven management technology to optimize resource allocation and enhance efficiency in all aspects of data center operations. Avant will meticulously design its HPC infrastructure to meet the demands of AI workloads, selecting high-performance CPUs and GPUs (or TPUs) specifically suited for deep learning tasks. This cutting-edge facility will enable Avant to accelerate AI advancements, delivering innovative solutions to clients by improving data center efficiency and empowering them with exceptional AI capabilities.
Additionally, Avant will implement a high-speed network to ensure efficient data transfer and select a scalable storage solution to manage the large datasets necessary for training and utilizing AI models. The HPC systems will prioritize security, incorporating robust measures to protect sensitive data and create a secure environment for AI deployment. Furthermore, the data center will integrate energy-efficient technologies and sustainable design practices, reflecting Avant’s commitment to environmental responsibility.
Avant Technologies also recently announced plans to implement AI-empowered Zero Trust Architecture (ZTA) across its data center operations. Additionally, the company has expanded its AvantAI™ platform to include intelligent, proactive monitoring and management for data centers.
Over the past few weeks Amazon.com, Inc. (NASDAQ: AMZN) has collectively committed to investing $20 billion into new data centers for its subsidiary Amazon Web Services (AWS). The first to be announced was an $11-billion data center to be built in Indiana, with another $9 billion set to accelerate cloud-infrastructure in Singapore. The moves fall in line with Amazon CEO Andy Jassy’s projection that 85% of IT spending will remain on premises, in the race for Gen AI supremacy.
Amazon also recently announced an extension on its partnership between AWS and CrowdStrike to unify cybersecurity protection on its CrowdStrike Falcon platform. As per the agreement, Amazon is replacing a variety of cloud point products with Falcon Cloud Security, is using Falcon Next-Gen SIEM to secure big data logging and is deploying Identity Threat Detection and Response to prevent identity-based attacks.
“CrowdStrike and AWS have a deep history of working together to secure the most innovative companies in the world,” said CJ Moses, Chief Information Security Officer and Vice President of Security Engineering at Amazon. “Amazon uses CrowdStrike to provide visibility, detection, and response across our businesses in order to protect the cloud, infrastructure, and services for our customers. This is part of our shared mission to help all organizations build, operate, and secure their business.”
In a move to shore-up its market position as a designer, builder, and operator of next-generation digital infrastructure designed for High-Performance Computing (“HPC”) applications, Applied Digital Corporation (NASDAQ: APLD) recently announced the appointment of industry veteran Todd Gale as its new Chief Development Officer. The announcement came just one month after the company announced it had issued a $50 million unsecured convertible debenture to advance its HPC Data Center Project in Ellendale, North Dakota.
“We intend to use the net proceeds from the private financing, supplemented by the proceeds from our announced sale of the Garden City facility, to finance substantial advancements in our construction phase of the HPC data center in Ellendale, North Dakota,” said David Rench, CFO of Applied Digital. “Concurrently, we continue negotiating our project-level financing to ensure timely project completion and fulfillment of our contractual obligations.”
Applied Digital intends to utilize chipmaking giant NVIDIA’s new Blackwell platform into its cloud offerings. The company’s next-generation data center campuses are specifically designed to host HPC/AI applications, offering more cost-effective and efficient alternatives to traditional data centers.
In Japan, Digital Realty Trust, Inc. (NYSE: DLR) recently announced the expansion of its NRT Campus, by commencing construction of its third data center to support AI. Upon completion of the site in late 2025, the campus’s capacity will rise to 104MW, with the intention of meeting rising demand for next-generation infrastructure, and seamless access to Japan’s connected data communities.
“Japan’s rapidly increasing demand for AI deployments creates the need for scalable, flexible, and highly connected AI-ready data centers in the Tokyo metropolitan area,” said Serene Nah, Managing Director and Head of Asia Pacific, Digital Realty. “We believe NRT14’s next-generation data center infrastructure and Digital Realty’s connected global open data center platform provide the foundational pillars our customers need to drive innovation in the coming years.”
Equinix, Inc. (NASDAQ: EQIX), another digital infrastructure company, has recently launched a $600 million joint venture with PGIM Real Estate to develop and operate the first xScale data center in the US, situated in California’s Silicon Valley. This follows their successful collaboration on the first xScale data center in Australia in 2022, which was part of a similar $575 million joint venture announced in 2021.
Under the terms of the new agreement, PGIM Real Estate will hold an 80% equity interest in the joint venture, while Equinix will retain a 20% equity stake. xScale data centers by Equinix enable hyperscale companies to expand their core deployments within Equinix’s IBX data centers, facilitating growth in over 70 global metros through a platform that supports direct interconnections with more than 10,000 customers.
This joint venture complements Equinix’s existing hyperscale collaborations in Europe, Asia-Pacific, and the Americas, significantly enhancing the global xScale data center portfolio. Once completed, this global expansion is set to exceed $8 billion, encompassing more than 35 facilities and providing over 725 megawatts of power capacity.
Source: https://usanewsgroup.com/2023/10/26/unlocking-the-trillion-dollar-ai-market-what-investors-need-to-know/ 
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Lucinity Wins the Microsoft Partner Awards for 2024 for Partner of the Year – Iceland and Sustainability and Social Impact

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REYKJAVÍK, Iceland, May 28, 2024 /PRNewswire/ — Lucinity, a leading AI company for financial crime prevention, won two awards at the Microsoft Partner Awards for 2024, including Partner of the Year – Iceland and Sustainability and Social Impact, highlighting Lucinity’s innovations and contribution to positive societal change. 

“Congratulations to Lucinity for being recognized as the Partner of the Year – Iceland 2024! Lucinity is leading digital transformation and delivering innovative products in their domain,” says Microsoft’s leadership.
“For the past year, they have played a key role with their offerings, skilled resources, and their ability to drive change and innovative solutions both locally in Iceland and across the globe. Lucinity has had significant social impact and growth while supporting our joint customers in their AI-transformation journeys.”
In June 2023, Lucinity launched the world’s first copilot for FinCrime prevention powered by Microsoft Azure OpenAI called Luci. Luci stands out in the financial services industry with specialized skills for FinCrime prevention such as adverse media checks, case analysis, and SAR writing. 
Built on the robust and scalable Microsoft Azure platform, Lucinity offers customers a trusted SaaS product. Additionally, Lucinity’s presence on the Microsoft Azure Marketplace allows companies to leverage their Microsoft Azure credits to access the platform. 
The seamless integration with Microsoft’s Azure stack has enabled Lucinity to implement advanced AI capabilities, fostering rapid innovation and enabling banks and fintech companies to utilize AI securely and audibly. Furthermore, Luci significantly reduces investigation times from 2.5 hours to just 25 minutes, saving Tier 1 banks an estimated $25 million annually.
Guðmundur Kristjánsson (GK), Lucinity’s Founder and CEO comments, “These awards are a testament to the strength and reliability of our solutions, made possible by our strategic partnership with Microsoft. Utilizing Microsoft Azure, we have been able to drive rapid innovation and create a robust, scalable platform that meets the rigorous requirements of compliance teams.” 
On the Sustainability and Social Impact Partner Award, Microsoft says, “Lucinity, with their innovative AI solutions, has really tried to combat this huge global challenge. They use ‘Human AI’ to enhance financial crime prevention, combining AI with human expertise for efficient, user-friendly solutions. Additionally, Lucinity has developed a tool called Luci, an AI-powered copilot that helps transform financial crime prevention from a process that took hours to one that takes minutes.”
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