Large Language Models (LLMs) exhibit impressive zero/few-shot inference and generation quality for high-resource languages (HRLs). A few of them have been trained on low-resource languages (LRLs) and give decent performance. Owing to the prohibitive costs of training LLMs, they are usually used as a network service, with the client charged by the count of input and output tokens. The number of tokens strongly depends on the script and language, as well as the LLM's subword vocabulary. We show that LRLs are at a pricing disadvantage, because the well-known LLMs produce more tokens for LRLs than HRLs. This is because most currently popular LLMs are optimized for HRL vocabularies. Our objective is to level the playing field: reduce the cost of processing LRLs in contemporary LLMs while ensuring that predictive and generative qualities are not compromised. As means to reduce the number of tokens processed by the LLM, we consider code-mixing, translation, and transliteration of LRLs to HRLs. We perform an extensive study using the IndicXTREME classification and six generative tasks dataset, covering 15 Indic and 3 other languages, while using GPT-4 (one of the costliest LLM services released so far) as a commercial LLM. We observe and analyze interesting patterns involving token count, cost, and quality across a multitude of languages and tasks. We show that choosing the best policy to interact with the LLM can reduce cost by 90% while giving better or comparable performance compared to communicating with the LLM in the original LRL.

Artificial intelligence (AI) has rapidly emerged as a disruptive technology with the potential to transform industries and societies. It is a branch of computer science that involves creating algorithms and models that can perform tasks that typically require human intelligence, such as natural language processing, image recognition, and decision-making. Leveraging AI can provide numerous benefits, including increased efficiency, accuracy, and cost savings. In this article, we will discuss how to leverage artificial intelligence in various domains and industries. Before diving into the specifics of leveraging AI, it's essential to understand the different types of AI.

Artificial intelligence (AI) is changing the way we live and work, and its impact is only going to grow in the coming years. Here are 10 ways in which AI is transforming our lives: Personal Assistants: AI-powered personal assistants like Siri and Alexa are already popular, and their capabilities are expanding rapidly. These assistants can help us with everything from setting reminders to ordering groceries. Healthcare: AI is being used in healthcare to improve diagnosis, predict outcomes, and develop new treatments. AI-powered medical imaging can detect tumors and other abnormalities, and AI algorithms can predict patient outcomes and identify high-risk patients.

Artificial intelligence (AI) is transforming the way we work, and the finance department is no exception. Chat GPT-4, developed by OpenAI, is a machine learning-based language model designed to understand and generate text in response to user queries. It is emerging as a new tool capable of assisting finance professionals in their daily tasks. After a week of testing Chat GPT-4 on various daily use cases within financial departments, OpenAI's solution stands out for its ability to adapt and offer relevant solutions in various contexts. The presentation of our test results is divided into two parts.

Artificial Intelligence (AI) is changing the world as we know it, and it is quickly becoming the most significant technological revolution of our time. It has already transformed many industries, from finance to healthcare, and its impact on the workforce has been widely discussed. As AI technology advances, it is likely to automate many of the tasks that were previously performed by humans, leading to job losses and significant changes in the labor market. In this article, we'll explore the industries that are likely to be most affected by AI and the jobs that are at risk. The manufacturing industry has long been a vital part of the global economy, but it is also one of the most labor-intensive industries.

Artificial intelligence (AI) is a rapidly growing field that has captured the attention of scientists, engineers, business leaders, and policymakers worldwide. It refers to the development of computer systems that can perform tasks that typically require human intelligence, such as learning, problem-solving, perception, and decision-making. AI has the potential to transform various industries and sectors, including healthcare, transportation, education, manufacturing, and finance, among others. In this article, we will explore the importance of artificial intelligence in the future and its potential benefits and challenges. One of the most significant advantages of artificial intelligence is its ability to automate routine and repetitive tasks, allowing humans to focus on more complex and creative work.

In the world of digital product design, innovation is a key factor in the success of any business. Companies need to keep up with the latest trends and technologies to remain competitive and stay ahead of the curve. Digital product design is an essential part of the process, as it helps to create products that are both user-friendly and effective. In this blog post, we'll take a look at the role that digital product design plays in innovating for the future. Digital product design is a great way to ensure that products are innovative and efficient.

High AI training costs have been a significant barrier to AI adoption, preventing many companies from implementing AI technology. According to a 2017 Forrester Consulting Report, 48% of companies highlighted high technology costs as one of the primary reasons for not implementing AI-driven solutions. However, recent developments have shown that AI training costs are rapidly declining, and this trend is expected to continue in the future. According to the ARK Invest Big Ideas 2023 report, training costs of a large language model similar to GPT-3 level performance have plummeted from $4.6 million in 2020 to $450,000 in 2022, a decline of 70% per year. Let's explore this trend of declining AI training costs further and discuss the factors contributing to this decline.

With Microsoft Bing amped up with its own generative artificial intelligence (AI) chat programming, there is little doubt that we are now in the era of AI being publicly part of our world. All the hype aside, will AI-type chat become as pervasive as we are hearing? I believe we will certainly get there, but there is still a long road ahead before it can be done successfully. Digital transformation is the process of using digital technologies to fundamentally change the way a business operates, delivers value to customers, and achieves its objectives. With, at best, only 26% of digital transformation being successful, what can leaders do to make sure they succeed when incorporating new digital tools?

With Oracle Fusion Applications for finance and supply chain, myTVS can integrate and digitalize processes, enhance business insights, and improve decision making to support future expansion. It has selected Oracle Fusion Applications to improve financial insights and better match inventory with customer demand. "myTVS is a leading digital aftermarket AI platform that provides a unique business model by decoupling customer value chain and delivers digital services to 3 million customers, 20,000 retailers and 25,000 garages across the country. We needed to integrate data across all our brick & mortar stores, and digital platforms to improve real-time insights, optimize business processes, and reduce costs. With Oracle Fusion Applications, we can standardize processes and create a single source of truth to improve the speed and quality of decisions and enable our organization to quickly respond to changes in supply and demand," said G. Srinivasa Raghavan, Managing Director for myTVS.