Democratizing AI is all about empowering others to use it, by making it available to them. Audiences, such as marketers in a company, will be able to access AI capabilities as part of their MarTech solutions, without the need of being technical. It could also be schools, where the younger generations are learning how to use it in responsible, secure, innovative, and creative ways. This is the year where companies, after discovery phases and teams experimenting, are looking to activate and take advantage of the AI advances. Generated with Microsoft Designer   And so, questions emerge, such as “What to democratize when leveraging AI?” There are common scenarios, as well as specific ones, that will depend on the company, and the industry they belong to. A common scenario, seen in many industries, when democratizing data is the data visualization and reporting . In digital marketing, as an example, data scientists and data analysts can automate reporting, making them available to the clien

 Recently, the European Parliament voted and passed the landmark EU AI Act. It's the first of its kind and sets a benchmark for future AI regulations worldwide . The EU AI Act lays the foundation for AI governance, and it's pertinent for organizations delving into AI systems to comply with the legislation, build robust and secure AI systems, and avoid non-compliance fines.  Photo by Karolina Grabowska via Pexels My three key takeaways from the legislation are as follows: The Act introduces the definition of an AI system: "An AI system is a machine-based system designed to operate with varying levels of autonomy and that may exhibit adaptiveness after deployment and that, for explicit or implicit objectives, infers, from the input it receives, how to generate outputs such as predictions, content, recommendations, or decisions that can influence physical or virtual environments" The Act introduces the classification of AI systems based on risk to society. The Act outlin

 Open source models will continue to grow in popularity. Small Language Models (SLMs) are smaller, faster to train with less compute.  They can be used for tackling specific cases while being at a lower cost.  Photo by Tobias Bjørkli via Pexels  SLMs can be more efficient SLMs are faster in inference speed, and they also require less memory and storage.    SLMs and cost Small Language models can run on less powerful machines, making them more affordable. This could be ideal for experimentation, startups and/or small size companies. Here is a short list Tiny Llama. The 1.1B parameters AI Model, trained on 3T Tokens. Microsoft’s Phi-2. The 2.7B parameters, trained on 1.4T tokens. Gemini Nano.  The 6B parameters. Deepseek Coder

On this occasion we would like to present our take and summary about prompt engineering. Like everyone else, at Beolle we have been researching the AI space lately, running experiments. On this occasion, our investigation has made us present our take and summary about prompt engineering. ( Skip Ahead note : If you like to get right to it then skip to the section What are prompts .) Generated image with Microsoft Designer and DALL-E 3 + Modified by Beolle team   (Parenthesis)  AI has disrupted all industries, and it will continue to do so as we explore new territories. We are still in discovery mode. Sectors and industries are building their know-how, evolving and using this technology;  determining the value it brings to the business. The investment by tech players and executives, in traditional and Gen AI (Generative AI) capabilities, continues rising. The consequence has been an accelerated growth in a short matter of time. Venture capital investment in AI has grown 13x over the las

Recently I was at a Christmas party and I found myself giving advice to a friend on being more productive. I shared the approaches that I take which helped me become more productive at work and in my personal life. The conversation with my friend inspired me to share my approaches in this blog .  Photo by Moose Photos from Pexels   My productivity framework has five key pillars and to remember them I use the mnemonic, POFOR = P lan your tasks, O rganize yourself, F ocus on your tasks, O ptimize yourself with habits and R eflect to ensure you are being productive on the right tasks. Plan Planning is very crucial as it sets the tone for the rest of the pillars. I always found I was more productive when I planned my tasks compared to when I didn’t, and hence planning has become my rule of thumb. I recommend taking 30 minutes at the end of each day to plan your next day. This means prioritizing your tasks and blocking your calendar accordingly. By not doing so, you are at risk of others

Gmail and Yahoo Mail recipients can comprise over 65-70% of an organization's email target lists. Hence, organizations must ensure they prepare for the upcoming requirements for Gmail and Yahoo Mail for senders. Recently, Google and Yahoo jointly announced they will implement stricter controls to ensure their users receive relevant emails and can unsubscribe effectively.  Photo by Solen Feyissa on Unsplash   In this article, we summarize these upcoming Gmail and Yahoo Mail requirements and provide resources for additional readings if you choose to explore further. Key date: According to Adobe, Google and Yahoo Mail will implement these requirements in Feb 2024.   There are three (3) essential requirements 1. Authenticate your email sending domain We wrote a detailed article on the three pillars of Email Authentication in Essence of email deliverability - SPF, DKIM, DMARC and segmentation . In summary, Google and Yahoo will require the sender domain to have proper authentications,

You have probably read that one of the many good things about OKRs is that it provides structure and clarity to work towards common goals. It helps connect company, teams and individuals’ objectives to measurable results.   Photo by Garreth Brown via Pexels In a previous Beolle article, Herak wrote about HOSKR and OKRs. In this iteration we will focus on the OKR scoring. Measuring the “How” The KRs in OKRs are the Key Results. With them we measure the progress towards the Objectives we have set. So how do we score them in a way that makes sense, and measure the success? Few “gotchas” before we start Grades are an indication where you're going. In OKRs, scoring between .6 to .7 is your target. Scores between .8 and 1.0 are rare, meaning they are not the usual. If you find yourself completing all your OKRs within this range then something is not correct, for example, your Objectives are not Ambitious enough, meaning you always knew you (or your company or your team) were going to ach

Generative AI continues to be front and centre of all topics. Companies continue to make an effort for making sense of the technology, investing in their teams, as well as vendors/providers in order to “crack” those use cases that will give them the advantage in this competitive market, and while we are still in this phase of the “AI revolution” where things are still getting sorted.   Photo by Google DeepMind on Unsplash I bet that Uncle Ben’s advise could go beyond Peter Parker, as many of us can make use of that wisdom due to the many things that are currently happening. AI would not be the exception when using this iconic phrase from one of the best comics out there. Uncle Ben and Peter Parker - Spiderman A short list of products out there in the space of generated AI: Text to image Dall.E-2 Fotor Midjourney NightCafe Adobe Firefly