Video Post: AI with BigQuery and SQL

Stop waiting to unlock the power of AI! 🤯 You already know SQL… and that’s ALL you need. Transcript if you have a lot of data stored on  Google Cloud for analytics it’s probably  going to be stored in B query now  everyone’s trying to do Ai and their  training models using pre-existing  models spending a lot of money on data  scientists but I’ve got some great news  if you’re using be query be query has be  query ml built into it this lets you run  AI against your B query data set by  using SQL now SQL is the language used  by all the people doing queries or  database administrators now it’s very  simple to use and you probably already  have the skills so you don’t need to go  and hire expensive data scientists and  AI Engineers to gather insights from  your data I’m going to break down some  of the models that are built into B cre  ml to see if these are going to solve  business problems for you first one is  linear regression this is predicting how  much you’ll sell based on past data so  if you’re planning stock Staffing trying  to run promotions more accurately this  is for you it’s built- in can be run  with sequel the next one is logistic  regression this is sorting things into  categories so let’s say you want to sort  customers into categories um to see  whether they’re going to buy from you  again um or if products are faulty  putting them into categories saying  these products are likely going to be  faulty so you can see the use cases for  business the next one is K means  clustering this finds hidden groups  within your customer base so you can  Target marketing campaigns towards them  the next Matrix factorization suggesting  which customers might be likely to buy  an it this is kind of what you’ll see  when you get predictive things on  websites saying and you might also like  to buy X I think we’re up to the fifth  one PCA or principal component analysis  this is simplifying complex data to find  the most important pattern helping you  spot Trends and make more informed  decisions the last one I’ve got is time  series so predicting future sales based  on past data helping you predict demand  and make sure you have enough stock  based on things that have happened in  the past so all of these models are  already build into big query ml as I  said and can be accessed using SQL  queries which you likely already have  the skills for in your organization to  enabling your organization to make AI  enabled decisions without spending an  absolute Fortune if you want help with  any of this Reach Out aviat Consulting  can help you thanks   – Generated with https://kome.ai

Video Post: Google Cloud Vertex AI & Hugging Face

Who Really Owns Your App? Transcript did you know that most app developers in Australia don’t let you own the IP that they develop for you let me break that down for you you pay someone to write an app for you they let you use it licensed to use it commercialize it change it but you don’t actually own the intellectual property now what would happen if someone else had a similar idea to you went to the same app developer they could sell the code that you paid them to develop this other person doubling their money the next day all they need to do is change the colors and logo maybe make a few slight changes and you’re going to have a competitor now the app developers made a ton of cash on this cuz they’ve sold the same thing twice and only done the work once but you’ve got a competitor that’s going to compete with you and I don’t think that’s really fair and that’s not what we do at aviato at aviato if you pay us to develop your app you own the intellectual property we aren’t going to steal it and use it elsewhere and we’re not going to sell it to a competitor a few days after we finish your project so that then you have someone to compete with in the marketplace if you are looking to get an app developed this is really something that you should be checking with the app developer that you’re going to use reach out to us if ou do want to get an app developed Thanks

Navigating the AI Maze

The AI landscape is exploding with a dizzying array of models, from the Large Language Models (LLMs) most of us have experimented with like Llama 2 or 3 from Meta, Claude 2 from Anthropic, and Bard (now Gemini) from Google, and the original ChatGPT. Each boasts unique capabilities, from generating different creative text formats to translating languages and answering your questions in an informative way. To make this even more confusing we have models that excel at robotics, tabular regression, image generation, or depth estimation. Choosing The Right Model For Your Business While this abundance offers exciting possibilities, it also presents a significant challenge: choosing the right model for your specific needs, and doing it within your budget. The pricing models for these vary greatly Gemin 1.0 advanced, to 1.5 Ultra is a 10x cost differential. For businesses, this creates an impossible puzzle: how do you select the optimal model without getting lost in the ever evolving AI arms race? And how do you do this within your budget? The answer lies in flexibility. Instead of locking into a single model, businesses need an adaptable infrastructure that allows them to test their business use case against one model, evaluate the performance and then try another, without rebuilding the solution. Additionally as new models are released, testing these to see if there is an uplift to the value of the model quickly, is going to give you the competitive advantage over others that need to rebuild their solution. This ability to quickly swap out models offers several key benefits: Architecture Architecting a solution that works for your business can be easily acheived on Google Cloud with Vertex AI, but this will exclude you from using ChatGPT or other models not avaiable on Huggingface.co LLMs on Google Cloud Vertex AI Google Cloud’s Vertex AI provides the perfect platform for achieving this flexibility. It allows businesses to seamlessly deploy, manage, and experiment with various LLMs through a unified interface. If you are not happy with the 50 or so models they have, you can deploy one from Huggingface.co which has over 600,000 models to choose from. The alternative solution for the non Google customers could be to write a common API, which would give you the flexibility to swap out models, or use Chat GPT which is one model that you cannot find on either Google or Huggingface.co Any LLM With a Common API Either option empowers you to leverage the strengths of different models, test each of them against your unique problems, and stay ahead of the curve in the rapidly evolving AI landscape. Aviato Consulting, a Google Cloud Partner, specializes in helping businesses navigate the complexities of AI and implement flexible LLM solutions on Vertex AI. Our expertise ensures you harness the full potential of AI, maximizing its value for your specific business needs.

Aviato,Your Google Cloud Partner for AI

The AI revolution is here, and businesses that embrace its potential stand to gain a significant competitive edge. However, navigating the complex world of AI can be daunting. That’s where Aviato Consulting, a trusted Google Cloud Partner, steps in to guide your business through a successful AI journey on Google Cloud. Unlocking AI Potential with Aviato and Google Cloud: Why Choose Aviato Consulting: Examples of AI Use Cases Aviato Can Help Implement: Embrace the AI Future with Aviato and Google Cloud: Partner with Aviato Consulting to unlock the transformative power of AI for your business. Leveraging Google Cloud’s advanced AI technologies and Aviato’s expertise, you can gain a competitive edge, optimize your operations, and drive innovation. Let us be your trusted guide on your AI journey.

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