"Up close and personal with AI: Learning from the tech"
Self-Testing Approach by Andrei Belevtsev: "Before introducing a product to the market, we personally test our offerings first"
Let's set the record straight: 'Artificial Intelligence', while it translates from English, doesn't fully cover the concept. 'Intelligence' and 'intellect' have slightly different definitions, leading us to imagine AI as a human-like entity. But it's essential to discuss what this technology can teach us or how to use it effectively. It's like diving into the ocean, exploring the vast digital depths with the help of one of the latest generative models, like GigaChat, available in various formats across Russia.
Your interaction with AI is guided by your instructions. Make sure to specify what you want from the model, define the role it should play, the type of responses you expect, and any preferred formatting or language style. Be thorough in outlining what the model should and shouldn't do. After that, you can creatively use it—say, have it simulate a job interview using a job description, with the AI acting as the HR interviewer. It can structure questions, listen to your responses, offer feedback, and point out areas for improvement.
"GenAI: The Swiss Army Knife of Technologies"
We've entered the era of generative artificial intelligence at breakneck speed because GenAI has become a general-purpose technology, similar to electricity. Picture this: a single technology with countless applications, just like electricity. The same generative model, GigaChat for business, can work as a solicitor, healthcare provider, procurement specialist, financier, developer, and more. And it's all the same model: it can see, it can hear, it can understand language, and it can respond.
This marks a major difference from previous technologies. In machine learning's heyday, we needed to train a specialized model for each specific task. Only a few companies could afford this path, with data scientists gathering, preparing data, and other tasks. But now, a universal model can handle such tasks, and data scientists are only required for complex cases where the model might lack knowledge or skills.
"Spreading the Knowledge"
We're all about sharing our technical advancements and experiences with partners. First, it all starts with knowledge. Find out about the technology, and try it out – initially on platforms like GigaChat on the web and Telegram. For more structured learning, consider educational courses offered by SberUniversity or corporate programs. It's crucial to understand how GenAI operates, which will inspire ideas on how to use it in various processes.
Step Two: Shaping Your Hypotheses for Business Benefit
Once you've gained a basic understanding, it's time to delve deeper and formulate crucial hypotheses for your business. Encourage every employee to present and implement ideas, and teach them to evaluate the effectiveness of these ideas. This is a critical skill—the ability to construct and test hypotheses is a fundamental aspect of scientific or technological experimentation.
Introducing innovation into a corporate landscape is a complex task that requires a well-designed system and attention to the security of your data and the agent solutions you create. Ideally, a system should be designed to evolve and adapt to new tasks and digital trends for years to come.
To help businesses, we've published a document on developing and implementing AI agents in corporate landscapes, sharing our insights and practices at Sberbank. This information will be valuable to many large companies. If you're a smaller business, you can leverage open-source software interfaces (APIs) to use the model without implementing it on your own.
"Experiment, Experiment, Experiment!"
Knowing what leading global GenAI developers can currently achieve is important. Experiment with everything, but once you've discovered what works, decide what to integrate. At this stage, companies must determine who to collaborate with for integration, who's responsible for the Service Level Agreement, and what the contingency plan is if something goes wrong. It's vital to decide who you're willing to work with.
Secondly, for trials, foreign software interfaces might be useful. However, for long-term integration into your business processes, consider if you're comfortable with a foreign model that may stop working at any moment, potentially interrupting the work you've done. Or do you require dependable, long-lasting solutions?
We believe that it's more critical to focus on the quality of the solution you're building and designing, beginning with the quality of data and integration, followed by how you're structuring the system itself. Of course, the model, as the core element, will always be key, and initial stages of implementation may require adjustments to ensure the model meets your requirements. Work closely with your partner to improve the system, add new integrations, and improve the model's performance in your specific domain.
"Encourage collaboration and knowledge sharing among companies through events like CIPR, where we exchange ideas, both successes and failures, and discuss the challenges faced by each company. This mutual exchange of information, both positive and negative, is invaluable experience. I'm a firm believer in cloud solutions. In countries with high cloud penetration, technological advancements are progressing at a rapid pace. Cloud solutions are faster, more reliable, and ultimately cheaper. We partner with Cloud.Ru, which provides cloud infrastructure for all our services.
Regardless of whether our projects are implemented on-premises or in the cloud, we're ready to offer solutions for large clients on their own premises and for companies seeking the perfect balance between speed and cost savings in the cloud."
"GenAI, the Swiss Army Knife of Technologies, is revolutionizing the landscape by acting as a versatile tool akin to electricity, capable of performing various tasks such as serving as a solicitor, healthcare provider, or financier. This universal model, like GigaChat, embodies technology's potential in data-and-cloud-computing and artificial-intelligence, transcending the boundaries of traditional, task-specific models."
"In the pursuit of innovation, it's essential to delve deeper and formulate hypotheses for business benefit, as every employee presents and evaluates the effectiveness of ideas. By implementing experimentation in an evolving, secure system, companies can harness the power of GenAI, ultimately spreading knowledge and collaboration among businesses for mutual growth and success."
