The Future of Retail: Exploring the Transformative Power of AI

In recent years, the use of artificial intelligence in the retail industry has become increasingly popular, with many big tech companies implementing the technology to enhance customer experiences and streamline operations. According to Yahoo Finance, the global AI retail market size is expected to reach $25.83 billion by 2028 from $5.19 billion in 2022.

Customer service stands out as the most prominent retail application for AI technology, with Amazon being one of the major investors in this domain. Amazon's Alexa Chat Bot is powered by a combination of natural language processing (NLP), machine learning (ML), and automatic speech recognition (ASR) technologies. When a user types a request into the chatbot, the ASR technology converts the text into a digital format that can be analyzed by the NLP algorithms. The NLP algorithms then analyze the syntax, grammar, and context of the user's request to determine the most appropriate response. In the meantime, the ML component enables the system to learn and improve over time based on users’ interactions: The more users interact with the chatbot, the better it becomes at understanding their needs and providing accurate responses.

Also, Alexa's AI-powered shopping assistant uses a combination of algorithms and data analysis to provide customers with product recommendations. In addition to that, the chatbot can also handle other types of requests, such as answering questions, placing orders, and providing customer with 24/7 support, meaning that they can to shop whenever they want without needing human assistance.

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AI is also being used by e-commerce companies to improve search results and product categorization. Alibaba, one of the largest e-commerce platforms in the world, uses AI-powered image recognition technology to automatically categorize products based on their visual characteristics, and uses NLP to analyze product descriptions and categorize them based on the words and phrases used. This allows the platform to identify product attributes and features even if they are not explicitly listed. Additionally, Alibaba has launched a virtual assistant, AliGenie, which uses AI to help customers with their shopping experience providing them with more personalized recommendations which are tailored on user’s preferences.

According to Yahoo Finance, AI market size was valued at $95.60 billion in 2021 and is projected to reach $1,847.50 billion by 2030, growing at a CAGR of 32.9% during that period. The use of AI in retail is becoming increasingly popular, and many big tech companies are developing new features to enhance customer experiences and streamline operations. Chatbots, virtual assistants, product recommendations, search optimization, and categorization are just some of the ways that AI is being used in ecommerce. As AI technology continues to evolve, we can expect even more innovative use cases to emerge, leading to improved customer experiences and increased efficiency in the ecommerce industry.

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The information in this article should not be regarded as a description of services provided by Delian Partners SA. The opinions expressed in this article are for general informational purposes only and are not intended to provide specific advice or recommendations for any individual or on any specific security or investment product. It is only intended to provide education about the financial industry. The views reflected in this article are subject to change at any time without notice.

Unlocking the Potential of ChatGPT

Artificial intelligence has seen significant growth in recent years, driven by advancements in Machine Learning and Natural Language Processing (NLP). One of the most notable developments in NLP is the rise of large language models such as ChatGPT.

ChatGPT, which stands for "chat-based Generative Pre-training Transformer" is a language model developed by OpenAI that is trained to generate human-like text. Over the last three years, ChatGPT was trained on 175 billion parameters and 300 billion tokens, equivalent to 570 GB of content from sources like Wikipedia, social media, news, and articles. The real breakthrough of ChatGPT is its user-friendly, open-source model that is freely available, making it a widely accessible, general-purpose sophisticated chatbot capable of writing like a human.

OpenAI has partnered with several companies to integrate ChatGPT into their applications. Microsoft, who invested $1bn in OpenAI three years ago, recently announced an additional $10 billion investment to incorporate ChatGPT into its products and make it widely accessible. Microsoft can use ChatGPT in a variety of ways, some examples including NLP for language understanding in products such as Cortana, Microsoft Teams, and Office; Text generation for products such as Word, PowerPoint, and Outlook to assist with writing and formatting documents and emails; Language Translation for products such as Microsoft Translator and Microsoft Edge to improve the accuracy and fluency of its language translation and make communication between users with different languages more seamless; Chatbot for customer service to develop a more natural and efficient communication between users and the products; and more.

With the increase in popularity of ChatGPT, many have started wondering if this could threat or replace Google’s search engine business. ChatGPT and Google have some similarities, such as a user-friendly interface and both help users get valuable information. However, it’s important to note that ChatGPT is not designed to search and retrieve information like Google's search engine does: The model is more focused on generating text based on a given context, but it does not have the capability to find and index the information from the internet. Also, while ChatGPT is focused on generating answers based on specific input, Google offers a wider range of services and products like cloud storage, email, and more. Although ChatGPT can assist users with tasks, it is unlikely to pose a significant challenge to Google in the near term as they serve different purposes and have different capabilities.

In addition, Google has also developed proprietary LLMs that are as advanced or more, than GPT, but have not made it available on an open-source basis. LaMDA, which stands for “Language Model for Dialog Applications” is a supervised-learning model and a “Google-equivalent” of ChatGPT. LaMDA is more accurate and broader in scope than ChatGPT, as it is trained on 540billion parameters, 3x that of ChatGPT. Also, Google uses a vast amount of internal data, giving LaMDA access to a larger data set to train its model compared to competitors, which gives Google a significant advantage in terms of quality and diversity of data available for training.

The future for ChatGPT is clearly promising: The model took only 5 days to hit its first 1 million users, while Instagram and Netflix took 3 months and 3.5 years respectively to reach the same target, making it the fastest-growing tech platform ever. As of today, the model is estimated to have an error rate of 2-5%, according to Bloomberg. But as with any technology, the costs and errors associated with using ChatGPT are likely to decrease over time as the model is further developed and optimized. The growth and popularity of ChatGPT are not expected to end soon, as the technology continues to advance, and more companies and organizations look to integrate the model into their products and services.

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The information in this article should not be regarded as a description of services provided by Delian Partners SA. The opinions expressed in this article are for general informational purposes only and are not intended to provide specific advice or recommendations for any individual or on any specific security or investment product. It is only intended to provide education about the financial industry. The views reflected in this article are subject to change at any time without notice.

SaaS: A Mandate for Companies Looking for Innovation

Today, Software-as-a-Service refers to a huge number of digital solutions that allow companies to externally manage, own, and deliver software, and represents one of the fastest-growing segments of the economy.

SaaS uses the Cloud infrastructure to store data and allow users to access the service via the internet browser, from everywhere and without the need to download anything. One of the major benefits is that software never goes out of date, just keeps getting updated.

SaaS penetration has accelerated in recent years, disrupting almost every sector and vertical you can think of. E.g., Netflix has become the leader of the SaaS providers in the entertainment industry, with a subscription-based streaming service providing users with an infinity of movie and tv series accessible from any device, notably bankrupting established market leader Blockbuster Inc. In recent years many other companies embraced the Netflix business model and introduced their streaming services, such as Disney+, Amazon Prime Videos, and Sony LIV.

Tekion is disrupting the automotive industry by providing the first and fastest cloud-based and end-to-end automotive SaaS platform, including all functionalities of a dealer management system (DMS). Tekion was founded by the former CIO of Tesla, who was responsible for building Tesla’s digital and information systems and software platform of the EVs company. When he launched Tekion, he aimed to make the car buying experience more efficient while increasing profitability.

Tekion provides dealers with the IT infrastructure through which they can manage inventory, keep track of customers’ leases, sell additional services to clients, and review loan options. By efficiently communicating with all the key stakeholders in the automotive sector – dealers, car manufacturers, and customers- the platform provides a rich and unified consumer experience while avoiding losing valuable information. In addition, the platform keeps updating over time thanks to cutting-edge technologies such as Machine Learning, Artificial Intelligence, and IoT. Tekion’s shareholders include established automotive companies such as Hyundai, BMW, and General Motors.

Because of the huge amount of data to be stored in the cloud, companies may experience difficulties in managing and monitoring all the flows of information. End-to-end software Datadog helps companies by providing an integrated monitoring and analytics platform to process information in real-time and across different clouds. Flexibility and accessibility today are not just a benefit, but a mandate for companies that want to scale up globally and be able to adapt their business to rapid environmental changes. Datadog is used by companies of all sizes and industries, and it aims to increasingly democratize the use of the various tools offering an integrated interface where different teams can create, monitor, and gain valuable metrics on the company’s activities.

As reported by Gartner, the SaaS industry is worth about $145bn, and it is expected to experience its largest annual growth in 2022, reaching a value of $171.9bn by the end of the year. The benefits of the SaaS model are evident, and many companies are making the transition to a subscription-based service: By 2026, it is predicted that 50% of organizations will integrate SaaS application.

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The information in this article should not be regarded as a description of services provided by Delian Partners SA. The opinions expressed in this article are for general informational purposes only and are not intended to provide specific advice or recommendations for any individual or on any specific security or investment product. It is only intended to provide education about the financial industry. The views reflected in this article are subject to change at any time without notice.