Responsible Al practices for business leaders
Dr. Rachel Adams, CEO, GCG
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The aviation industry is expanding rapidly, making it imperative to adopt sustainable practices. Airports worldwide are taking significant measures to reduce their carbon footprint, conserve natural resources and encourage social responsibility but still more needs to be done.
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The aviation industry contributes to global carbon emissions, with airports accounting for about 2-3% of that contribution. While this is not very significant and airports are committing to Net-zero, they impact the environment in many other ways. Airports consume significant amounts of energy and water and generate waste equivalent to small cities and contribute significantly to noise pollution leading to health disorders in the neighbourhood. Airports also promote economic growth through trade, tourism, job opportunities, support for local businesses, and regional development and hence a sustainable balance is the need of the hour.
Airports around the world are recognizing the importance of sustainability and are implementing various eco-friendly initiatives to reduce their ecological footprint. Four key areas of focus have emerged: energy, waste, water, and noise. Some leading airports have already implemented sustainable initiatives, such as using recycled materials for construction and mandating the use of reusable tableware in food and beverage establishments. Emerging ideas include hydrogen fuel cells and bio fuels (for energy), AI and IOT Sensors for optimal water usage, hydrothermal liquefaction and AI/ML to detect recyclables for waste and AR safety programs and Noise insulation techniques for Noise impact reduction. Others need to assess their current state and take steps that best suit their situation. Download Complete Research
Credits
Author@lab45: Deepika Maurya
17:48 Minutes The average duration of a captivating reports.
The banking sector is experiencing significant changes primarily driven by the growing integration of technology into consumers’ daily lives, evolving customer expectations, increasing interest in digital money and the volatility of cryptocurrencies. The potential annual value of AI and analytics for the global banking industry is expected to be as high as $1 trillion.
Credits
Lead Authors@lab45: Deepika Maurya, Chandan Jha
Contributing Authors@lab45: Sujay Shivram, Hussain S Nayak
11:39 Minutes The average duration of a captivating reports.
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.
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
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