Alina Cristina Buteica, L&D and HR Expert, Founder & CEO at Illuminated Essence & Growth Hives, spoke on the topic of “Conscious Development of Generative AI in Business”.
Challenging the audience with the question of whether we are at the peak… or just the beginning of Generative AI innovation, the speaker mentioned examples of businesses that are at the forefront of this area: Unbabel (helping companies deliver multilingual customer experience at scale) and Wild.AI (the Generative AI app that elevates the capabilities of the female body).
The entrepreneur also mentioned RedBridge Lisbon – the Entrepreneurial & Investors club bridging Lisbon & San Francisco, which has dedicated its activity to organizing events on AI & Business: Champalimaud Center, Lisbon; Shack15, San Francisco; RedBridge Palacio, Lisbon; TechCrunch Article after event with Unbabel.
Speaking about the case for Human-Led, Earth-Conscious (Generative) AI, Alina Buteica said that everyone should get involved in shaping the future of AI – we shouldn’t just leave AI to the experts (as it impacts our future). She also said that we should promote a responsible use of AI, promote compassion for the environment, human life, and all forms of life, as well as a biomimetic and ethical AI, which is at the service of our planet and human life.
“Nature without AI would still be a beautiful place… But AI without nature, living in a totally artificially generated/manufactured world… Is a frontier not to be crossed, for our greater good”, concluded the speaker from the third panel.
Filipe Marques, Chapter Lead at Data Analytics and AI at Siemens, brought to Q-Day an example of a successful case implemented in the company where he works: “ai:express – Automated Generative AI and Chatbot Deployment”.
Bearing in mind that at Siemens, “we aim to make LLM accessible to everyone, providing a platform that can be customized to cater to the unique needs of each business”, the speaker explained that this experience was born from the challenge of having a framework for domain adaptation across Siemens units, making it accessible to everyone.
In this way, ai: express emerged, with a user-friendly interface suitable for non-coders and security, integration with Siemens Cloud services, compatibility with various LLM models, and support for various file formats and URL parsing. What’s more, it is being tested for different use cases: Ai attack assistant, RolandUnplugged, SGES Topic Modelling, Conference Summarization, Integrated Management System Documentation, and Siemens Data Cloud, exemplified by the speaker on the third panel.
Hugo Cartaxeiro, Founder & Managing Partner at Singularity Digital Enterprise and Urbiwise – Property Markets Analytics, began by presenting a brief history of AI development, focusing on the differences between AI Parameters and the Human Brain, as well as the importance of Large Language Models: “LLM are unique in their ability to generate high-quality, coherent text that is often indistinguishable from that of a human”.
The speaker then addressed the topic of Generative AI Business Impact, saying that “Generative AI is set to unleash a powerful wave of productivity growth that is likely to affect all industries and could add up to 4.4 trillion dollars a year to the global economy”.
Regarding the importance of being a first mover, the entrepreneur said that these ‘champions’ are characterized by their competitiveness (early-access to cutting-edge research, tools, and platforms to create innovative solutions and products); impact (by solving some of the most pressing challenges and opportunities); growth (by automating and optimizing processes and also refreshing business culture with new ways of working and thinking); and learning capacity (different perspectives and experiences by expanding knowledge and skills).
Liliana Ferreira, Director of the Fraunhofer Research Center for Assistive Information and Communication Solutions in Portugal, dedicated his presentation to “The Future of Artificial Intelligence” topic.
Having previously explained why Artificial Intelligence is not Machine Learning, the speaker quoted Picasso – “Computers are useless. All they do is provide answers”, to clarify that “Generative AI is a tremendously powerful assistant. Humans have the responsibility to query the AI, and therefore to control its activity and to verify the relevance of its output”.
Liliana Ferreira recalled that AI currently does a number of tasks well: generating reports, supporting brainstorming, detecting anomalies or specific activities, segmenting information, translating texts, generating content from different data sources, “reading” images, creating transcripts, etc. But AI is not always used with good reasons, stressed the speaker, listing some cases of fake news, bots, trolls, or micro-targeting.
To conclude her participation in the third panel, Liliana Ferreira recalled the importance of projects such as the Center for Responsible AI and Artificial Intelligence Certification, which make it possible for data provenance and governance, traceability, accountability, and transparency.
João Ferro, Chief Technology Officer at Quidgest, began by saying that, “at Quidgest, we believe model-driven development shapes future-ready software” and “in the realm of Generative AI, models take center stage”. The speaker of the third panel, seized the moment to highlight some of the benefits of the Genio platform. The Quidgest platform is capable of automatic code generation, thanks to its model-driven development approach, resulting in ready-to-use solutions. Did you know that through the use of AI, Genio’s automatic code generation goes from the traditional human programmer rate of 3 bytes per second to a staggering 1,000,000 bytes per second? The benefits for business owners are clear: faster time to market, improved collaboration, and reduced development costs.
According to the speaker, there’s nothing to fear when it comes to traditional software developers losing their jobs: “Let Genio handle the repetitive part of coding, while you focus on making the valuable parts”. By using the creative capabilities of Generative AI and combining it with the predictability of an Inference Engine, we could tackle the biggest faults of both models and enable the creation of application models by prompting, instead of manual definition.