Aruna Pattam

8️⃣6️⃣📈 We surveyed the Australian Data & AI ecosystem late last year and saw 86% of respondents answering their core data assets were in ‘acceptable’ state of worse! Let that sink in, to understand what that means for data-driven reporting, BI, and AI. It has a few logical implications: 1️⃣After pulling a dataset from a database data needs significant further labour intensive curation for any meaningful business or artificial intelligence reducing both ROI and time to value for Data & AI. 2️⃣Organisations will revert back to biased decision making, either by using personal experience from leaders, or based on generic market insights from management consultants often based on terrifying assumptions You start seeing why I personally moved from management consulting to data consulting? Our world is in dire need of less biased decision making. For more, read our State of Data & AI report: https://lnkd.in/gwCHiD_x

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This comprehensive new report from CSIRO in Australia explores the case for the creation of sovereign AI foundation models, given their dependency on models developed elsewhere - a similar situation to the current state here in Aotearoa. Elanor Huntington, CSIRO Director of Digital, National Facilities & Collections says "But they are rarely made in Australia. The vast majority come from the United States and China. Our industry is becoming increasingly dependent on these models. On one hand this is an opportunity. All these great tools are appearing at our fingertips. But there is also risk. Will these models boost the competitive interest of Australian companies and workers? Will they behave according to our norms, cultural and ethical expectations? Can we be adapting, fine-tuning or building our own AI foundation models to support our own industry and workers? If so, how should we go about doing this? What's Australia's best placement in the global value chain for AI foundation models? There are many more questions. And we are at the beginning of a journey" While not relying on or endorsing its output, the report also puts the same questions and challenges to ChatGPT and provides a transcript of that conversation - an interesting addition to the report. https://lnkd.in/gxC3wuP8 #genAI

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AI Product Lifecycle Governance Critical updates to Australia's AI Governance Framework have recently been released to ensure greater safety and fairness for Business, Government and Consumers. This is the start of improved transparency and will enable Industry and Government to be able to scale more safely and fairly.

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📢 Hey friends of Data Sciences and Machine Learning, I'm looking for a speaker for Perth Machine Learning Group to share ideas, learnings, experiments and knowledge for the August Meetup (In-person). DM me for more details. If you have a vague idea of what you might want to present, ping me anyway! I'll help you polish it! #AI #ML #LLM #SpeakingOpportunity

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𝗔𝗜 𝗦𝗲𝘁 𝘁𝗼 𝗕𝗼𝗼𝘀𝘁 𝗔𝘂𝘀𝘁𝗿𝗮𝗹𝗶𝗮'𝘀 𝗘𝗰𝗼𝗻𝗼𝗺𝘆 𝗯𝘆💲2️⃣0️⃣0️⃣ 𝗕𝗶𝗹𝗹𝗶𝗼𝗻 🚀🚀 Australia stands to gain immensely from #AI, with a potential $200 billion yearly boost to GDP and 150,000 new jobs by 2030, says a new report by Professor John Mangan from the University of Queensland. It highlights the urgency for Australia to enhance AI integration in sectors like tech and healthcare to remain competitive. The report urges increased funding for AI research and skill development to ensure Australia doesn't fall behind global AI advancements. https://lnkd.in/gixSjvrh #AI #ArtificialIntelligence #Technology #Innovation #FutureofWork #DigitalTransformation #AIinAustralia #AIstrategy #AIleadership #AIresearch #AIeducation #AIpolicy #AIimpact #AIethics #AIdevelopment

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Qlik’s new #AI Council (launched January 2024) on stage, Day 2 keynote at #QlikConnect. Left to right, Dr. Rumman Chowdhury, Kelly Forbes, Dr. Michael Bronstein, Nina Schick, James Fisher. Chowdhury: Because AI are trained to be helpful specifically within the user’s own context, when we use AI “we unintentionally create our own filter bubbles [and] socially engineer our way into disinformation.” This is an important point as we pursue #trustworthyAI! The #generativeAI user experience necessarily engenders trust that isn’t inherently deserved. It also emphasizes the point that generative “AI” is a misnomer: it isn’t “intelligence,” it’s 𝘴𝘪𝘮𝘶𝘭𝘢𝘵𝘪𝘰𝘯. These AI are trained to provide answers that APPEAR helpful (among a few other characteristics)—but cannot be trained to provide answers that 𝘢𝘳𝘦 𝘵𝘳𝘶𝘵𝘩𝘧𝘶𝘭

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Join us for a Generative AI workshop on June 12th in Sydney where we will be covering the fundamentals of GenAI, intermediate behaviours like Semantic Search, and advanced behaviours involving LLMs. https://gag.gl/Lix3z4

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Navigating the journey from pilot projects to scalable production in #GenAI is filled with challenges and will require a strategic and disciplined approach. A rough estimate is that only 10% of the pilot projects scale in large enterprises. Focus needs to be on business value, establishing a standard GenAI #platform, change management, and cost management. A recent #McKinsey article talks about steps required to scale. I appreciate the article's emphasis on the need for a GenAI platform that integrates within the enterprise tech stack. It's not just about #LLMs. More focus is needed on such architecture and evolving patterns. The tech stack illustration effectively highlights how various capabilities – like orchestration, semantic search, data extraction, guardrails, and prompt engineering - come together to create a robust GenAI solution. The future expansion of the agentic workflow will further enhance this architecture. Link to the article in comments.

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