Keith Aumiller

Venice.ai shows the future of what GPTs will be like, and how they will be fully private and uncensorable. It is a known fact that each of the big GPTs (ChatGPT, Gemini, etc) have various types of manipulation and skew answers. Venice.ai has no barriers when it comes to a political agenda. I would envision that at a future point, many people will use these types of GPTs, and pay for them using Bitcoin or another cryptocurrency. No government or organization can stop a bitcoin payment, and in countries where there is censorship and limited (or no) freedom of speech, these GPTs will become a way around these restrictions. #gpt #chatgpt #generativeai #ai #dataculture #artificialintelligence https://venice.ai/home

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Agents: Redefining Generative AI’s Potential 🤖 Generative AI is evolving beyond static capabilities—are you keeping up? Humans thrive on logic, reasoning, and tools to solve complex problems. Now, Generative AI models are doing the same by transforming into agents—intelligent systems that don’t just generate text but actively: ✔ Access real-time data (like a customer’s purchase history). ✔ Make informed decisions based on reasoning and logic. ✔ Execute actions such as sending emails, retrieving information, or even automating transactions. This shift unlocks game-changing opportunities for businesses and individuals alike. Imagine AI agents that: 🌟 Enhance customer experiences with tailored solutions. 🌟 Streamline operations by automating repetitive tasks. 🌟 Integrate seamlessly with APIs to complete tasks autonomously. 💡 Curious about how it all works? Our whitepaper dives deep into how Generative AI agents combine reasoning, tool integration, and self-directed capabilities to reshape the future. 📄 Download the PDF now and stay ahead of the curve. The future of automation, intelligence, and action is here. Don’t let others leave you behind. 💬 What’s your take on AI agents? Let’s discuss in the comments! #GenerativeAI #AIInnovation #AIAgents #FutureOfWork #Automation #ArtificialIntelligence #AIIntegration #NextBigThing #AIRevolution

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Very useful article to explain that vector similarity or closeness or lower distance doesn't necessarily always mean relevancy. This understanding is very handy when we deal with issues in RAG (Retrieval Augmented Generation) use cases. The article featured 3 libraries that we can potentially use to gauge context relevancy (Ragas, DeepEval and TruLens) and how their capabilities differ one from another. When I studied AI at NUS-ISS, NLP (Natural Language Processing) topics in the last semester were the most fascinating for me since it shows how math can be used to extract meaning or important features from human language. https://lnkd.in/gH2Pf-25 #llm #genai #nlp #ml #ai

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Snowflake Agrees to Acquire Open Data Integration Platform, Datavolo. Empowering data engineers with hybrid, multimodal pipelines, and open source flexibility. Connectors incoming!

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Every hour of the day presents different opportunities for your productivity, especially when it comes to your data systems and workflows. The reality is that system performance ebbs and flows, often outside of our control of inputs we have to consider. What process do you and your data-minded colleagues use to tackle your most important and valuable tasks so the noise doesn't sidetrack you? Your answer can reveal a lot about the efficiency of your workflows and data systems and how well your team navigates bottlenecks or downtime. 🛠️ Many teams focus solely on technology—new tools, bigger databases—but is that really what drives productivity? Or is it knowing how to pick your priorities? The key isn't just in having the best-marketed tools out there. How do you optimize your work to get the most out of your data? Let’s share strategies. 🚀👇 #DataStrategy #TechProductivity #SystemsEfficiency #ETLOptimization #DataDrivenDecisions

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Chances are you didn't invent the database. But there are still so many ways you can use one to automate what you do. Automating makes it simpler to get things done, gives your work more credibility (you took the time to automate it, so you show that your time is valuable), and primes you and prepares you to make incremental improvements. #automation #efficiency #productivity #dataanalytics

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I have just learned that polars has a glimpse function. Glimpse: "Return a dense preview of the DataFrame." This is a great function for viewing the DataFrame in a neat format.

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AI models are becoming increasingly expensive to train, with ChatGPT-4 costing up to $74 million more to make than ChatGPT-3. Why? The increasing complexity of these models and the way they're delivered to the public means developers need more time and resources to create them, pushing up the cost. What does this mean for me? It may seem like opportunities to engage in AI development are dwindling due to increasing costs. However, there is tremendous work being done with open source models that might reverse this trend. Zooming out. If costs continue to rise, this could lead to fewer voices influencing AI development, making it more difficult to achieve ethical and equitable AI. Similarly, LICs may struggle to access new models, further widening the digital divide. #AI #EthicalAI #TechTrends

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👉🏼 Does using artificial intelligence take the person out of personal statements? We can't tell 🤓 Jenna N Whitrock 👇🏻 https://lnkd.in/eApWGiGv 🔍 Focus on data insights: - 📊 Only 59% of AI-generated personal statements were correctly identified by participants. - 👩‍⚕️ 60% of AI-generated statements were rated as the best, while 43.3% were labeled the worst. - 📝 A significant 66.7% of participants opposed the use of AI in personal statement writing. 💡 Main outcomes and implications: - 🚫 Concerns about the reliability of distinguishing AI-generated content raise issues for the integrity of residency applications. - 🤔 The mixed perceptions towards AI usage could influence future policies regarding personal statement submissions. - 🔍 Insights suggest a need for better training or guidelines for evaluators to recognize the nuances of AI-generated text. 📚 Field significance: - 🏥 Highlights ethical considerations in surgical residency applications amidst technological advancements. - 🌐 Supports ongoing discussions about transparency and authenticity in medical education assessments. - 📈 Indicates a trend toward more stringent evaluation practices as AI becomes integrated into application processes. 🗄️: [#artificialintelligence #medicaleducation #surgery #personalstatements #ethics #residencyapplications]

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❓ Did you know that Tableau's character sort is case-insensitive?   ⚖️ That means that it treats capital letters and lowercase letters as the same.   👍 That's probably a good thing and a useful default.   😀 The (somewhat funny) problem that I ran into is that has my RDBMS (Teradata) has case-sensitive sorting.   📃Capital letters sort first, lower case letters later.   ❌ I was testing my dashboard with some queries against the source data and many of my metrics were off for the first row.   🔍 In the Teradata tool, the text fields were also being truncated for display as in the "Output" section of the image.   👁️ So initially, I couldn't see the sort disparity.   👍Once I saw it, I wrapped my ORDER BY with an UPPER(variable), which eased the comparison, and everything was fine.   📝 Sometimes it's the little things (assumptions) that cause problems.   🏗→🧠 Build to Learn!   💭🚶‍♀️🚶‍♂️ Follow for more.   #data #datascience #analytics #VizoftheRay

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A big focus in the data world is on data literacy, and ensuring that anyone in an organization has a basic level of understanding and can use data effectively. This led me to check on regular literacy in the US. I was frankly shocked by some of the statistics: ✅ Illiteracy has become such a serious problem in our country that 130 million adults are now unable to read a simple story to their children ✅ 45 million are functionally illiterate and read below a 5th grade level ✅ Between 46% and 51% of American adults have an income well below the poverty level because of their inability to read ✅ Illiteracy costs American taxpayers an estimated $20 billion each year There are quite a few other statistics, and I've included them in the link below. The implications of low literacy (or complete illiteracy) has very negative consequences for those individuals, our economy, healthcare, etc. We've come a long way as a country when it comes to literacy, but there is still room for improvement and we should be focusing more of our education efforts on basic literacy. https://lnkd.in/gCURvMSf

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AI has the potential to drive positive social change. However, the majority now believe that AI-powered chatbots and LLMs will actually increase economic inequality and lead to a consolidation of power. Why? Existing regulation isn't ensuring that AI tools and their benefits are being distributed fairly. This is already making it difficult for small businesses and LMICs to access them, putting them at a disadvantage to large corporations and HICs. What does this mean for me? We're at a pivotal moment in AI development. If nothing changes, many of us will see ourselves negatively impacted in some way. Disenfranchisement may increase, and we may find ourselves economically worse off. However, we can prevent this. Engaging with regulators, governments, and developers around the world will help us develop systems that ensure AI benefits everyone. Zooming out. Several LMICs have seen significant growth in the last few years, and we've been making steady progress towards equality. However, a lack of action now will see this come undone as AI becomes increasingly embedded into society. #Inequality #AI #FutureOfSociety #EthicalAI

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Good article. We’re really excited about how we’re driving our BI strategy by taking a strong, governed approach that uses analytics on analytics and makes the most of our BI metadata. It’s all about making sure our data is not just secure but also super useful for everyone By focusing on good governance, we’re creating an environment where our BI tools are efficient and safe to use. Using analytics on analytics helps us get a clear picture of how everyone is using the tools and data. We can see who’s accessing what, spot trends, and find ways to make things even better—basically, it’s about optimizing our resources On top of that, by tapping into BI metadata, we’re gaining insight into the story behind our data. It’s not just about the numbers; it’s about understanding where the data comes from and how it all fits together. This helps us create a more user-friendly experience that encourages everyone to explore the data while keeping everything trustworthy We are still on the journey but future of BI will be those that can harvest and promote safe and impactful artifacts of a federated developer communities. https://lnkd.in/exQPEa4H

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What do we get wrong as data leaders? Predictability. Let me explain. When your business partners ask you how long it is going to take to build a dashboard, what do you say? Commonly, you'll hear a range (like 4-6 weeks). And, also commonly, something throws a wrench in this range and it has to be extended. What about when it comes to investment decisions? For how example, how much will this new data platform cost? We think it will cost $1 million, and then after implementation it was actually $1.75 million. Businesses (and business partners) crave predictability. Now the detractors will say "data is too complicated for this" or "it's impossible to forecast exactly how much investment we'll need." Guess what? I don't buy it. If large technology companies can forecast out their financials, and can set dates for product releases, why can't you? Predictability is a way that a data team will have greater credibility and more likely to be treated as another business team. The more that you can do this as a data leader, the greater success you will see. #data #dataculture

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In 2023, the number of people using AI tools rose to 250 million, more than double the number of users in 2020. However, it's not necessarily the tools we use that create value, but the way we use them. AI absolutely can be used to boost productivity. LLMs, for example, can help people complete work up to 73% faster. They can also boost the quality of work when used as a 'provocateur'. This involves using LLMs to challenge assumptions to give knowledge workers to think outside the box. This isn't just a chance to boost productivity; it's a chance to widen our perspectives and increase the diversity of our thinking. On a larger scale, this will transform the way we work. It will make knowledge work more fulfilling by creating cultures of lifelong learning. It also has the potential to create more inclusive workplaces by encouraging people to embrace new ways of thinking rather than resisting them. #AI #Productivity #CriticalThinking

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AI is expected to automate at least 18% of jobs and drastically change others. So what's driving this? The rapid development of AI is seeing new use cases and opportunities, and companies are eager to jump on these. Zooming out, this trend will cause significant disruption and LICs will be the hardest hit. AI-driven automation will increase the productivity of HICs but exacerbate the digital divide, putting countries that don't have access to this technology at an even greater disadvantage. What does this mean for you? For most of us, this will create some sort of instability. Whether it be total job loss or simply making some of our skills redundant, AI will change the job market, which makes reskilling one of the best ways we can prepare. With this in mind, one of the most important skills to develop will be algorithmic literacy. This will help us to use AI by giving us a better understanding of how it works, which will also make it easier to identify novel use cases. At the same time, it will also allow us to develop AI in a safe and ethical way, creating a better future for all. #Skills #AI #AlgorithmicLiteracy #NewSkills

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