Understanding the key differences between Azure Databricks and Azure Synapse Analytics can help you select the best platform for big data analytics.

Unlocking Big Data: Azure Databricks vs Azure Synapse

Presented by platformeconomies.com: These heavy-weights Analytics solutions are as much partners in crime as they rival each other. Learn in this podcast what to look after - and read more about what matters managing data at scale in my book: https://a.co/d/gK7YzOL

Databricks VS Snowflake VS Microsoft Fabric

Hello and welcome to AI Tech News Today! I'm Aurora, your host, and I'm here with my co-host Isabelle. Today is January twenty-third, twenty twenty-five, and we have some intriguing headlines in the world of artificial intelligence to cover. So let's dive right in!

Musk slams Trumps $500B AI plan. In a recent announcement, former President Donald Trump launched a jaw-dropping initiative dubbed The Stargate Project, aiming to set up a massive five hundred billion-dollar artificial intelligence data center. Teaming up with SoftBank, OpenAI, and Oracle, each will contribute one hundred billion dollars to the pot. However, Elon Musk was quick to criticize this ambitious plan on social media, claiming that SoftBank isn't financially capable of making such a significant investment. Amid this spat, Sam Altman from OpenAI invited Musk to visit the project's first site, implying that Musk's priorities might be misaligned with national interests.

LinkedIn violates users' private data? Another headline that has raised eyebrows involves LinkedIn, which is being sued by US Premium customers. The lawsuit alleges that LinkedIn shared private messages and InMail data with third parties for training their artificial intelligence models—without proper consent. An added twist is that LinkedIn had introduced a privacy setting that automatically opted users in. Their updated privacy policy came under fire, as it indicated data sharing would not be affected retroactively, showcasing a worrying trend about user privacy in tech.

Meta x Databricks strategic partnership. Moving on to collaborations, Meta recently participated as a strategic partner in a ten billion dollar funding round for the data analytics platform, Databricks. This partnership is expected to blend Databricks' capabilities with Meta's advanced resources as Databricks looks to expand its reach into international markets, leveraging their own Large Language Model to provide a more robust data analytics solution.

And before we wrap up, here’s a reminder to keep an eye on the evolving landscape of artificial intelligence. The developments we've discussed today are just a few examples of how AI is shaping industries and influencing our daily lives.

Thank you for joining us today! Stay tuned for more updates and insights into the fascinating world of artificial intelligence. Until next time, this is Aurora and Isabelle signing off!

Musk Challenges Trump’s $500B AI Initiative as LinkedIn Faces Privacy Lawsuit and Meta Invests in Databricks

Hello everyone! This is Aurora, and welcome to AI Tech News Today. In this podcast, we bring you the latest happenings from the world of Artificial Intelligence. Let’s dive right into today's top stories.

OpenAI’s Operator AI agent automates web tasks with a browser. OpenAI has introduced an innovative feature called Operator, which allows its Artificial Intelligence to perform tasks directly in a web browser. This new functionality lets the AI engage with websites just like a human would—clicking, typing, and scrolling to tackle complex and repetitive online work. Imagine your assistant handling all those mundane tasks while you enjoy a cup of coffee!

Gemini 2.0 Flash thinking mode: Google’s new AI innovation. Google has launched Gemini 2.0 equipped with a Flash thinking mode that enhances its reasoning capabilities. This experimental model is designed to display its thought process step-by-step, giving users a clearer understanding of how AI arrives at its conclusions. It sounds like the AI is finally ready for a math test!

LinkedIn faces lawsuit over alleged AI training data use. The professional networking giant is now under legal fire in the United States. A lawsuit claims that LinkedIn shared users’ private messages with third parties for Artificial Intelligence training purposes without user consent. The suit seeks damages amounting to one thousand dollars per affected user. Looks like LinkedIn may have to brush up on its privacy policies.

Databricks raises fifteen point twenty-five billion dollars, valued at sixty-two billion dollars with Meta as investor. The data and analytics platform Databricks recently secured substantial funding that includes ten billion dollars in Series J equity and an additional five point twenty-five billion dollars through debt financing. Major financial institutions like JPMorgan Chase and Goldman Sachs are backing this deal, setting Databricks up for significant growth in the AI-driven data sector.

Samsung Galaxy S25 brings AI-integrated operating system and multimodal agents. The new Samsung Galaxy S25 series claims to offer the most context-aware and personalized AI experience yet. Powered by the new One UI 7.2 and the Snapdragon 8 Elite Mobile Platform, users can expect seamless interactions between their devices and various AI applications. Talk about a smart phone!

Thank you for joining us today! We hope you stay informed about the latest advancements in Artificial Intelligence. Remember, the future is here, and it’s not just smart; it’s brilliant!

OpenAI's New Browser Agent Automates Tasks, While Google Unveils Innovative Gemini 2.0 Amidst Legal Woes for LinkedIn and Major Funding for Databricks

" We did a survey with The Economist globally which obviously included Europe and APAC as well. And we asked the question, 'Does my organization's current architecture supports the unique demands of AI workloads.' Basically 85% said, 'No. We don't have the architecture to support it.' Some partially does, but it needs lots of modifications. So we can still feel a lot of people are still in the early stages and that data point ties back to: 85% of GenAI [proof of concepts] has not gone into production. I think that another interesting point is, 'Does your architecture connect AI application? -your relevant business data.' which is probably nearly even more important for me. Again, it was still about 80%- 'We don't have that.' Because that business data is all over the place. Without the clean data, you cannot get good AI." - Patrick Kelly 

Fresh out of the studio, Patrick Kelly, Senior Director for Digital Natives, Startups &amp; Enterprise and Commercial Sales in Southeast Asia at Databricks, joins us to discuss how data intelligence is powering enterprise AI applications in ASEAN. Beginning with his career journey from network engineering to tech leadership across Asian markets, Patrick explained how Databricks pioneered the Lakehouse architecture and integrated generative AI into enterprise workloads. Emphasizing the critical role of data quality in AI success, he showcased compelling customer case studies from across ASEAN and revealed striking generative AI trends in Asia - notably that 85% of organizations lack proper architecture to support AI workloads, reinforcing that clean data remains foundational for effective AI implementation. Patrick concluded by sharing his vision of what success looks like for Databricks in Southeast Asia. 

Audio Episode Highlights: [00:46] Quote of the Day #QOTD [01:49] Introduction: Patrick Kelly from Databricks [02:28] Career journey from network engineering to technology sales leadership [06:43] Lessons from Patrick's career journey [09:10] The Data &amp; AI total market opportunity in Southeast Asia and How Databricks is poised to capture the market. [10:08] How Databricks pioneered the Lakehouse concept, combining data lake and data warehouse capabilities. [15:24] The One Thing that Patrick know about Databricks that very few do. [17:52] Customer success stories from Grab, GetGo, GovTech to Siam Commercial Bank [22:50] How Mosaic AI positioned Databricks to develop enterprise-quality AI solutions with customers. [27:29] Key Trends in Asia Pacific on Generative AI. [32:23] The Importance of Data Architecture for Enterprises adopting AI. [35:13] Advice for Businesses on Implementation of AI [37:25] What does great look like for Databricks? [41:40] Closing remarks and invitation to the Data and AI Summit. 

Profile: Patrick Kelly, Senior Director for Digital Natives, Startups &amp; Enterprise and Commercial Sales in Southeast Asia at Databricks. 
LinkedIn: https://www.linkedin.com/in/patrick-kelly-aab6168/ 

Podcast Information: Bernard Leong hosts and produces the show. The proper credits for the intro and end music are "Energetic Sports Drive." G. Thomas Craig mixed and edited the episode in both video and audio format. 

Here are the links to watch or listen to our podcast. 
Analyse Asia Main Site: https://analyse.asia 

Analyse Asia Spotify: https://open.spotify.com/show/1kkRwzRZa4JCICr2vm0vGl Analyse Asia 

Apple Podcasts: https://podcasts.apple.com/us/podcast/analyse-asia-with-bernard-leong/id914868245 

Analyse Asia YouTube: https://www.youtube.com/@AnalyseAsia 

Analyse Asia LinkedIn: https://www.linkedin.com/company/analyse-asia/ 

Analyse Asia X (formerly known as Twitter): https://twitter.com/analyseasia 

Analyse Asia Threads: https://www.threads.net/@analyseasia 

Sign Up for Our This Week in Asia Newsletter: https://www.analyse.asia/#/portal/signup 

Subscribe Newsletter on LinkedIn https://www.linkedin.com/build-relation/newsletter-follow?entityUrn=7149559878934540288

How Databricks Revolutionize Intelligent Enterprise AI in ASEAN with Patrick Kelly

Fresh out of the studio, Nick Eayrs, Vice President of Field Engineering for Asia Pacific and Japan at Databricks, and Simon Fassot, General Manager and Head of Global Data and Analytics at Hafnia, join us to explore how data intelligence is transforming enterprise AI across diverse industries in Asia. Nick explained the fundamental distinction between general intelligence and data intelligence - emphasizing how enterprises gain competitive advantage by training AI on their proprietary data rather than public knowledge. Nick showcased customer success stories including Standard Chartered Bank and TechComBank and shared his perspectives on how senior executives can take advantage of AI by moving fast rather than wait and see. Last but not least, Nick offered what great would look like for Databricks in Asia Pacific and Japan in serving their customers. Adding the lens of the customer, Simon shared Hafnia's transformation from legacy SQL Server systems to a unified Databricks architecture serving their global shipping operations and elaborated on how the company is breaking down silos with their data supermarket and "Marvis" AI copilot for maritime operations based on retrieval augmented generation. 

"I think the biggest trap to potentially fall into is, "Hey, it's moving so fast, so much is changing. Let's just wait it out." Completely the wrong approach. You just gotta get started." Nick Eayrs from Databricks

"As tech people within the shipping industry, how do we explain, how do we make it accessible to all our users? So that's where we came up with the idea of a data supermarket, with in mind really the target of enabling self-service for our business. So by giving the analogy of a supermarket, it was much easier at the beginning to explain our business." - Simon Fassot from Hafnia

Episode Highlights:
[00:00] QOTD by Nick Eayrs and Simon Fassot
[00:49] Introduction: Nick Eayrs from Databricks
[03:32] Customer obsession means deeply understanding their business context
[05:22] Data intelligence versus artificial general intelligence explanation begins
[06:42] AI trained on your data creates competitive advantage
[08:17] Only 15% of companies have correct AI infrastructure ready
[11:17] Don't wait for AI perfection, just get started now
[12:30] Agent Bricks simplify AI development using natural language
[18:32] Shared responsibility model for ethical AI deployment
[25:24] Asia Pacific psychology focuses on future, not past
[26:28] Most important question: How do you get started?
[30:18] What does great look like for Databricks?
[33:16] Introduction: Simon Fassot from Hafnia
[35:18] How Hafnia transformed to full cloud architecture centralizes data through Databricks
[36:28] Self-service access needed for 300 onshore, 4000 vessel employees
[41:32] Unity catalog controls data quality for AI cases
[42:21] Two-phase Gen AI: ingest unstructured, then consume data
[44:25] How to implement Generative AI: One bad AI answer loses all user trust
[45:31] How reports in Hafnia use RAG embedded in workflows
[46:47] Data supermarket analogy simplifies self-service for business
[48:39] Marvis AI personalizes Gen AI within company context 
[49:46] Neo4j partnership adds graph capabilities to ecosystem
[53:33] DNA Port platform unifies scattered dashboards and applications
[54:22] Databricks enables focus on business value over operations

Profiles:
Nick Eayrs, Vice President of Field Engineering, Asia Pacific & Japan at Databricks
LinkedIn: https://www.linkedin.com/in/nick-eayrs/

Simon Fassot, General Manager and Head of Global Data and Analytics at Hafnia
LinkedIn: https://www.linkedin.com/in/simon-fassot-68b95135/

Podcast Information: Bernard Leong hosts and produces the show. The proper credits for the intro and end music are "Energetic Sports Drive." G. Thomas Craig mixed and edited the episode in both video and audio format. 

#dataaiworldtour #databricks #enterpriseai #retrievalaugmentedgeneration #dataintelligence

The Truth About Enterprise AI & Why Data Matters with Nick Eayrs and Simon Fassot

Fresh out of the studio, Craig Wiley, Senior Director of Product Management at Databricks who leads Mosaic AI, joins us to discuss the forefront of enterprise AI from model development to deployment at scale. Beginning with his career journey in ML operations, Craig explained how he recognized the critical connection between data and AI layers that could deliver order-of-magnitude acceleration in development cycles. Emphasizing the transition from classical ML operations to LLM operations, he showcased how Databricks' unified platform eliminates training-serving skew through data lineage capabilities and supports both fine-tuning and RAG approaches depending on industrial use case requirements. Highlighting compelling customer success stories including Suncorp's employee productivity platform and AstraZeneca's transformation of 400,000 clinical trial documents into queryable insights, Craig revealed a striking reality about enterprise AI evaluation - that 85% of AI use cases are being evaluated only by the engineers who built them, reinforcing that proper evaluation frameworks remain foundational for trustworthy AI implementation. He concluded by introducing Agent Bricks as Databricks' evaluation-centric approach to building production agents, emphasizing that model flexibility and rigorous testing are essential for enterprises moving from experimentation to production, while sharing his vision that the industry must evolve from the "year of agents" to the "year of evaluation and quality."

"85% of AI use cases are being evaluated by the engineer who built it saying, 'yep, seemed to work pretty well.' If you're gonna build a system that's going to be critical to the business, that's going to be important that it gets it right, then you can't do that without evaluations." - Craig Wiley

Episode Highlights: 
[00:00] Quote of the Day by Craig Wiley
[01:21] How Craig Wiley started his work in ML Ops that led him to Databricks
[02:43] Data and AI layer connection creates order-of-magnitude acceleration
[03:47] Mosaic AI acquisition expanded Gen AI solution capabilities
[04:38] Classical ML statistics versus Gen AI evaluation challenges
[05:48] Mosaic AI covers end-to-end from data ingestion
[07:12] Training-serving skew eliminated through unified platform lineage
[08:51] Fine tuning versus RAG depends on use case
[10:49] Industrial agents benefit from fine-tuned smaller models
[13:52] Agent Bricks prioritizes accuracy over simplicity alone
[15:44] Model flexibility crucial for speed and accuracy optimization
[17:59] Suncorp and AstraZeneca demonstrate diverse AI applications
[19:37] Asia Pacific shows aggressive AI adoption strategies
[22:00] 85% of AI cases evaluated only by building engineer
[24:12] Industry terminology evolves rapidly from RAG to agents
[25:39] Customer creativity with governance capabilities inspires product development

Profile: Craig Wiley, Senior Director of Product Management at Databricks and Mosaic AI
LinkedIn: https://www.linkedin.com/in/craigwiley/

Podcast Information: Bernard Leong hosts and produces the show. The proper credits for the intro and end music are "Energetic Sports Drive." G. Thomas Craig mixed and edited the episode in both video and audio format. 

Here are the links to watch or listen to our podcast.
Analyse Asia Main Site: https://analyse.asia
Analyse Asia Spotify: https://open.spotify.com/show/1kkRwzRZa4JCICr2vm0vGl 
Analyse Asia Apple Podcasts: https://podcasts.apple.com/us/podcast/analyse-asia-with-bernard-leong/id914868245 
Analyse Asia LinkedIn: https://www.linkedin.com/company/analyse-asia/


#dataaiworldtour #databricks #enterpriseai #retrievalaugmentedgeneration #agentbricks #evalsAI #evaluationAI #MLOps

Agent Bricks and How Data-AI Integration Changes Everything with Craig Wiley

A weekly podcast dissecting the pulse of business, technology & media in Asia. Hear our host interviewing leading journalists, senior executives, respectable authors & thinkers, entrepreneurs & thought leaders to discuss the most important issues that move and shake the business landscape in the Asia Pacific. The show is originally created and hosted by Bernard Leong.

New tracks tagged #Databricks