📆 August 2nd 2024📆 

Welcome to our latest subscribers. I’m glad you have joined our little community that keeps growing every day. Please make your voice heard at the bottom of this newsletter and keep me aligned to what you need.

• I’ve been talking with clients lately and the elements of a successful AI projects have kept coming up. This is good, it means the hype is subsiding and realism is kicking in. But what makes a “good” AI project?

• After much waiting, OpenAI are finally rolling out Voice. The goal is to create a more immersive experience, time will tell

• Meta are following on the trail of AWS and announcing AI Studio where users can quickly customise AI chatbots for their own use

• Amazon report on a long running experiment to have stores with no tills. Using an impressive combination of sensors and models, customers can shop and have their receipt updated in real-time as they shop

• As always, too much to put in headlines. Check out the Other News Rollup section for a quickfire review of the top stories in AI.

Dive in for all the details!

🆘 Quick Tips 🆘 

If we thinking about using AI in your business as a journey, the actual AI is the last step. Think of it as making the climb up Machu Pichu, using AI is like walking through the sun gate but there are so many exciting experiences as you make that climb.

To ensure the highest chance of success for your data & AI investment consider the following points:

1. The Right Question - Are you framing the problem correctly, too often people lean on the problems that big tech talk about - but the right questions focus on a section of your business. So don’t ask “How can AI increase Sales?” but rather “How can AI free up 2 hours of my sales team’s week?”

2. Data Sourcing - Do you have the right data to achieve your goals? Without good data an AI is just a digital parrot - controversial maybe but it’s true. Knowing what data you have and what data you need to get is vital before taking a step.

3. Data Quality & Management - This can be the forgotten step. Even with the right question and the right data, passing through conflicting, inconsistent or just plain bad data is going to cause your AI project to produce unexpected results. This is one of the main drivers of ML & AI project failures. Having processes and systems to manage your data increases the chance of success.

4. Experimentation - This can be the hardest step to take since it has less certainty about the outcomes but I cannot stress enough how important it is. AI & ML are based in Data Science and leverage the concept of hypothesis based experimentation heavily. Put simply, while the goal may be defined the way we get there needs to be tested across multiple ideas. The tip here is not to have unchecked experimentation - have milestones and measure experiments against achieving those but you MUST experiment.

5. AI - Bringing the whole puzzle together, a question with the right data, managed in the right way & tested hypothesis equals a successfully deployed AI project. As you can see, the hard work is mostly unseen but is all important to the final deliverable.

Does this resonate? If it does and you would like to learn more about how you can get AI ready you can book a free 30 minute discovery call.

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📰 News 📰 

Create Your Own Custom AI Chatbots Today

Meta has introduced AI Studio, allowing users to create custom chatbots with unique personalities, including versions based on themselves. This tool, available to Instagram Business accounts and rolling out to all users in the US, enables creators to engage with fans through direct messages. Users can customize their bots' responses and limit interactions, while adhering to guidelines that prohibit impersonating real individuals. Meta aims to enhance user experience by offering personalized AI interactions, building on lessons learned from previous chatbot attempts.

Read More At: Wired

Inside Amazon's Just Walk Out Technology: Combining AI, Transformers, and Edge Computing

Amazon's Just Walk Out technology is revolutionizing the retail experience by eliminating the need for traditional checkout processes. This technology uses a blend of advanced computer vision, sensor fusion, and deep learning algorithms to allow customers to enter a store, pick up items, and simply walk out, with their purchases automatically charged to their account. The system employs high-resolution cameras and weight sensors on shelves to accurately track items taken by customers​​.

The backbone of this technology is an edge computing architecture that processes data locally within stores rather than relying entirely on cloud computing. This reduces latency and enhances reliability by minimizing data transmission over the internet​​. The technology can distinguish individual shoppers without using biometric data by assigning a temporary digital code to each customer, ensuring privacy and security​.

Read More At: VentureBeat

OpenAI Unveils Advanced Voice Mode for ChatGPT

OpenAI has begun rolling out its Advanced Voice Mode for ChatGPT, a highly anticipated feature that enhances the chatbot's interaction capabilities with more human-like expressions and faster response times. This update is available to a limited group of ChatGPT Plus subscribers as part of an alpha release. The new mode runs on the GPT-4o model, which reduces latency significantly compared to previous versions​​.

The Advanced Voice Mode allows users to engage in real-time conversations with ChatGPT using both voice and vision inputs. It features a streamlined processing method that uses a single neural network to handle voice-to-text transcription, processing, and text-to-voice conversion, leading to improved efficiency and quality of interactions​.

This development marks a step forward in making AI interactions more seamless and engaging, although it also raises concerns about potential misuse of such advanced technologies​.

Read More At: The Verge

🔨 AI Powered Tools 🔨 

• Before Sunset - Productivity tool designed to enhance workspace organization and focus. It provides an AI-powered ambiance generator to customize work environments, a Pomodoro timer to boost focus, and tools for task management, note-taking, and time tracking.

• Newo - Digital employee solutions to automate customer interactions in industries like hospitality and wellness. It uses AI to create personalized "Intelligent Agents" capable of handling tasks such as customer service, sales, and support. These agents integrate with corporate systems, learning from existing data to improve efficiency and enhance customer satisfaction.

• WriteSonic - Content creation platform offering a range of tools like AI writing assistants, SEO optimization, and AI chatbots. It is designed for marketers, agencies, and enterprises to generate high-quality content, enhance SEO, and engage audiences effectively. Writesonic leverages advanced AI to create factually accurate articles, automate SEO tasks, and provide real-time web search

🗞️ Other News Rollup 🗞️ 

Qualcomm's AI Growth - Qualcomm's Q3 2024 revenue rose 11%, driven by AI innovations in smartphones and PCs, despite market recovery concerns.

Meta's AI Future - Meta plans significant AI investments, aiming for Llama 4 to enhance user engagement and advertising efficiency.

GPT-4o Long Output - OpenAI's new GPT-4o Long Output model offers 64,000 tokens for enhanced user responses.

Smart Home Robots - MIT's RialTo enables robots to learn tasks efficiently using digital twins of home environments.

AI Comparison Tool - Google's new 'tab compare' feature in Chrome uses AI to streamline product comparisons across multiple tabs.

Wildfire Tracking Expansion - Google expands its wildfire tracking tool to 15 new countries in Europe and Africa to enhance community safety.

Gemma 2 2B Unveiled - Google's Gemma 2 2B AI model outperforms larger counterparts, emphasizing efficiency and accessibility in AI technology.

Guardrails for AI - Amazon Bedrock's ApplyGuardrail API ensures safe AI outputs through real-time content moderation and customizable policies.

Microsoft and OpenAI Dynamics - Microsoft's annual report reveals OpenAI as a competitor, signalling a shift in their long-term partnership amid regulatory scrutiny.

AI Act Compliance Challenges - The EU AI Act mandates compliance for AI technologies, especially in HR, raising concerns about innovation and regulatory burdens.

Microsoft's AI Earnings - Microsoft's Q4 2024 results show strong revenue, but investors question AI's immediate profitability impact.

Apple's AI Hardware Shift - Apple selects Google TPUs for AI model training, moving away from Nvidia hardware.

GPT-4o Privacy Concerns - GPT-4o's data collection raises privacy issues, but users can manage settings to protect their information.

AI Database Enhancements - Google Cloud enhances its database tools with AI features, improving data analytics and generative AI capabilities.

AI and Voice Actors - Voice actors strike against AI threats to their jobs, demanding fair protections and compensation from major gaming companies.

🎶 Prompts 🎶 

Prompts used to generate some of this issues images. Unless otherwise stated all images are using Dall-E and ChatGPT Plus.

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