Uncovering GenAI tools and infrastructure
Rajat Monga, Co-Founder, TensorFlow
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By acquiring 100+M users in first 3 months of launch, ChatGPT has brought the field of Generative AI (GenAI) into mainstream awareness. The adoption of ChatGPT and similar applications have positioned Generative AI (as well as “Deep Learning”) as the newest disruptive tech after cloud computing.
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After the internet, mobile and cloud, GenAI could become the next platform for the coming decade. It will improve productivity and base line the quality of output.
Generative AI, a field of Artificial Intelligence, refers to computational models that are trained on massive amounts of input data (300bn words in the case of ChatGPT). They can synthesize data, draw inferences and create new outputs in the form of text, images, video, audio, new data and even code.
Two architectures have made GenAI immensely valuable
ChatGPT, for instance, uses the transformer model along with Human Feedback Reinforcement training to generate high quality outputs. Training a model requires intensive computational power (supercomputers were used to train GPT3) and significant investments (OpenAI being a key example). But once a model is trained, it can be optimized for a larger user base. Download Complete Research
The market is expected to grow from $8B in 2022 to $109B in 2030 at a CAGR of 34.6%. Key facts as follows
Need for content synthesis
We generate ~2.5 quintillion bytes of data every day on the internet. This not only makes searching for information tough but also makes inferring tougher, for regular users. GenAI tools can search, synthesize and compose an answer.
Democratization of content creation
We are moving from a search and retrieval economy to an infer and compose economy. People used to prompt algorithms to search and retrieve information but now they can prompt algorithms to infer and compose information.
Instant economy
Digital natives prefer tools that enable instant creation of content e.g. Tik Tok. ChatGPT can generate a word in 350ms after processing database of 300B words.
Access to massive computational power
The ability to instantly process and compose information using cloud computing.
Evolution of deep learning neural networks
Large Language Models have become openly available. These models help organize much of the internet’s information and develop patterns to mimic human decision-making.
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GenAI will fundamentally change several functions in enterprises leading to improved productivity and performance of employees. A Few areas of business where it will have the biggest impact are as follows:
Content creation
Gen AI will lead to more automation in content creation. It will not only reduce the cost of content creation but also increase the quality & variety of content created. Generative AI based DIY Apps are expected to emerge for marketing and design functions.
Content personalisation
Marketing touchpoints like newsletter, websites, videos, metaverse etc. will get hyper-personalized. This will improve brand engagement and conversion ratio of the sales funnel.
Drug discovery
Drug Discovery is a time-consuming process that can extend to 5-12 years. Gen AI can help identify potential drug candidates and test their effectiveness using computer simulations, thus saving time in the process. It has already led to tremendous real-world value, when the first mRNA covid vaccines were developed by programming mRNA molecules to express the specific antigen response. By 2025, more than 30% of new drugs and materials could be systematically discovered using GenAI techniques, up from zero today.
Software development
IT products and services could see the biggest impact. Below are some scenarios that may unfold.
Credits
Lead Authors@lab45: Siddhant Raizada, Nagendra Singh, Tommy Mehl, Arvind Ravishunkar
Contributing Authors: Aishwarya Gupta, Anindito De
13:03 Minutes The average duration of a captivating reports.
Reusable rockets & satellite miniaturization collaboratively are democratizing access to space. Fuelling innovation across multiple domains and fostering a future where space is accessible to enterprises, individuals, and nations alike.
The section delves into the historical roots of the space race between the United States and the Soviet Union, highlighting its profound impact on technological advancements. It explores how the competition between these superpowers catalyzed innovations that have become essential in various industries, including telecommunications, healthcare, and more. The section also discusses how the end of the space race didn't mean the end of innovation but rather heralded a new era of technological advancements that continue to shape our world today.
This section focuses on the economic revolution brought about by the introduction of reusable rockets. It discusses how companies like SpaceX have drastically reduced the cost of space exploration by developing rockets that can be landed and reused. This has made space more accessible to not just governments but also private entities and educational institutions, thereby democratizing space exploration. Download Complete Research
The section provides an in-depth look at SpaceX's Falcon 9 rocket, one of the most iconic reusable rockets in the industry. It discusses its design, capabilities, and the groundbreaking technology that allows it to be reused, making space travel more economical and sustainable. The Falcon 9 serves as a case study for the potential future of cost-effective space exploration.
This section explores the trend of miniaturization in satellite technology, focusing on the development of CubeSats. These small, modular satellites have opened up new avenues for space exploration and commercial applications. Their smaller size and modular design make them more cost-effective and accessible, allowing for a wider range of applications and participants in space technology. Download Complete Research
The section discusses how CubeSats are revolutionizing agriculture by providing high-resolution imagery of farmland. This technology enables more efficient and effective resource allocation, transforming traditional farming methods. CubeSats are making precision farming more accessible, allowing for optimized use of water, fertilizers, and workforce, thereby making farming more sustainable and cost-effective.
This section delves into the additional innovations that CubeSats have enabled, beyond their initial applications. It discusses how these small satellites serve as testbeds for new technologies and scientific research, from studying Earth's atmosphere to testing new materials and communication technologies. CubeSats are paving the way for future advancements in space technology. Download Complete Research
The section explores the emerging business models in the space industry, particularly focusing on the 'As-a-Service' models. It discusses how these models are making space technology more affordable and accessible, from Data-as-a-Service to Mission-as-a-Service. These new business models have the potential to further democratize space technology, making it accessible to a broader range of participants.
Credits
Authors@lab45: Abhigyan Malik
Key contributors: Ariel Zajdband, Planet
13:30 Minutes The average duration of a captivating reports.
GenAI is transforming various domains including software engineering. This technology enables high productivity, rapid development, and abundant innovation promising overall productivity gains of 26-30%. Embrace the future and discover the extraordinary potential of GenAI.
GenAI is expected to boost productivity in software engineering by 28% and is projected to improve task completion speed by 54% by 2025. It can also increase application development and maintenance revenue by 25%-30%, leading to a 5%-6% improvement in overall profitability. The GenAI market is expected to grow at a CAGR of 42% over the next decade, and the technology can help address the expected shortfall of 4 million developers by 2025. However, detailed study and implementation strategies are needed to consider factors such as initial installation effort, resource training, and technology integration.
GenAI can significantly impact the various phases of software development by generating code, improving code quality, simplifying code structures, and automating tasks such as unit testing and bug detection. It can reduce the duration of task execution across various software development stages by 20%-45%, resulting in substantial cost savings. While software engineers may be the primary beneficiaries of GenAI, other teams, such as architects, consultants, and sales teams, can also derive substantial advantages. However, implementing GenAI requires a comprehensive strategy that includes tool selection, investment, deployment, and developer training. The implementation strategy should target the highest-leverage phases of software development, and enterprises should invest in resources and training necessary for developers to leverage the technology effectively. Download Complete Research
Integration of GenAI with DevOps principles can increase productivity by automating tasks, generating content, and providing intelligent insights. Adopting GenAI in the DevOps software development environment can further boost productivity through script generation, automated monitoring and alert generation, and synthetic data for pipeline load testing. GenAI can complement and enhance Low Code No Code (LCNC) capabilities by integrating visual developer interfaces, quickening development cycles, and creating text and multimedia assets. Key platforms for code generation using GenAI include Copilot by GitHub, CodeWhisperer by AWS, ChatGPT by OpenAI, Vertex AI by Google Cloud, and TabNine by Codota Dot Com Ltd.
As AI continues to evolve, GenAI will become an increasingly essential aspect of the software development process. GenAI provides opportunities for innovation and creativity while also presenting new challenges. Customized benchmarking contextualized to the customer environment is crucial in refining and optimizing GenAI tools, fostering greater productivity and efficiency in software development. Enterprises must formulate a comprehensive GenAI strategy and incorporate GenAI tools in the implementation and testing phases of the software development lifecycle to maximize development cost and effort savings and improve quality. Collaboration with GenAI tools will create new roles, such as Prompt Engineers, and allow developers to focus on strategic thinking and creative problem-solving. GenAI is also an excellent learning and training tool, automating the generation of educational content and assisting in information retrieval and organization. Download Complete Research
Credits
Lead Authors@lab45: Hussain S. Nayak, Anju James
Contributing Authors@lab45: Vinay Ramananda, Dattaram B A
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