Bengaluru:

Google said today that it is working with MeitY ‘Startup Hub’ to train 10,000 startups in artificial intelligence (AI), as the tech giant expanded access to its AI models and introduced new language tools for the developers in the country.

At its ‘I/O Connect’ event here, the company unveiled a range of tools, programmes and partnerships to empower Indian developers and startups to be at the forefront of the global AI revolution.

The company said that developers in India now have expanded access to Google’s powerful AI models with the two million token context window in Gemini 1.5 Pro and Gemma 2, the next generation of open models.

“We’re committed to empowering Indian innovators to harness AI’s full potential, creating solutions that not only address India’s unique needs but also shape the future of AI globally,” said Ambharish Kenghe, Vice President, Google.

The opportunities with multimodal, mobile, and multilingual AI are immense, and we’re thrilled to be a part of India’s AI journey, he added.

“The fastest way to build with Gemini is through its developer platform Google AI Studio, and India has one of the largest developer bases on Google AI Studio today,” said the company.

The Google DeepMind India team has expanded Project Vaani, in collaboration with the Indian Institute of Science (IISc), which provides developers with over 14,000 hours of speech data across 58 languages, collected from 80,000 speakers in 80 districts.

The team also introduced IndicGenBench, a comprehensive benchmark to evaluate the generation capabilities of LLMs on Indic languages, and open-sourced CALM (Composition of Language Models).

The company said it is introducing Google Wallet APIs to simplify the integration of loyalty programs, tickets, and gift cards.

For developers using the Google Maps Platform, India-specific pricing is being introduced with up to 70 per cent lower costs on most APIs.

Google is also collaborating with the Open Network for Digital Commerce (ONDC), offering developers building for ONDC up to 90 per cent off on select Google Maps Platform APIs.

“From consumer experiences to agriculture, to social enterprises, AI has the power to address some of the biggest challenges of our time across many sectors and industries,” said Seshu Ajjarapu, Senior Director, Google DeepMind.

The company will also soon launch the Agricultural Landscape Understanding (ALU) Research API, a limited availability tool designed to make agricultural practices more data-driven and efficient.
 

(Except for the headline, this story has not been edited by NDTV staff and is published from a syndicated feed.)

The Reserve Bank has ventured into Artificial Intelligence (AI) and Machine Learning (ML) analytics in multiple areas in order to develop cutting-edge systems for high frequency and real-time data monitoring and analysis, RBI Governor Shaktikanta Das said today.

In his address at the inauguration of the RBI’s 18th Statistical Day Conference, Governor Das said: “The focus now is naturally on enhancing capacity in AI and ML techniques and analysing unstructured textual data. While doing so, ethical considerations need to be addressed and biases in algorithms need to be eliminated.”

He said that this annual event provides an opportunity to reflect on the current and evolving state of the statistical system. It also helps to take stock of the refinements in the application of statistical methods and technologies in the realm of public policy.

“Looking ahead, the year 2025 has a special significance for the compilation of official statistics the world over. Global efforts are expected to culminate in new global standards for the compilation of macroeconomic statistics, especially for national accounts and balance of payments. Our team in the Reserve Bank is closely tracking these developments,” the RBI Governor said.

The surge in computing power is being increasingly harnessed in combination with statistical methods to improve efficiency in decision-making and enrich end-user experience in various fields of human knowledge, he added,

The celebration of Statistics Day in India coincides with the birth anniversary of Professor Prasanta Chandra Mahalanobis whose contributions in laying the foundations of modern-day official statistics in India have been pioneering. Inspired by his work, Indian statisticians are making their presence felt – both domestically and globally in traditional as well as in newer applications of statistics, he added.

Governor Das highlighted the areas in which the Reserve Bank’s cutting-edge information management is contributing to the formulation of public policies and the overall economic development in India.

“One year ago, we launched our next-generation data warehouse, i.e., the Centralised Information Management System (CIMS) at the Statistics Day Conference. Several new features were introduced in the new system. Scheduled commercial banks (SCBs), urban co-operative banks (UCBs) and non-banking financial companies (NBFCs) have already been onboarded for reporting on the new portal,” he said.

The new CIMS is also facilitating research on the Indian economy, minimising reporting burden, exploiting the technological advances and improving the experience of both data providers and users, Governor Das added.
 

(Except for the headline, this story has not been edited by NDTV staff and is published from a syndicated feed.)

New Delhi:

A new AI-based model could predict the onset of Alzheimer’s disease by analysing an individual’s speech, the developers said.

Trained on audio recordings of patients with mild cognitive impairment — early stages of memory loss, the model achieved 78.5 per cent accuracy in forecasting whether patients would remain stable or progress to dementia within six years, according to the researchers.

Alzheimer’s disease is the most common form of dementia and impacts one’s everyday activities by impairing memory and thinking.

The researchers at Boston University, US, used recordings of initial interviews of 166 patients aged 63-97 and trained the model using machine learning to discern patterns between speech, demographics, diagnosis, and how their condition was worsening.

The model analyses interview content such as spoken words and sentence structure, rather than speech features such as enunciation or speed, showed the study published in the journal Alzheimer’s and Dementia.

“We combine the information we extract from the audio recordings with some very basic demographics – age, gender, and so on – and we get the final score,” said Ioannis C. Paschalidis, a professor of engineering and the study’s corresponding author.

“You can think of the score as the likelihood, the probability, that someone will remain stable or transition to dementia. It had significant predictive ability,” said Paschalidis.

The researchers said that the model was able to perform well, despite challenges like low-quality recordings and background noise.

The researchers emphasised that early prediction is crucial as current diagnostic tests often identify Alzheimer’s disease only after significant cognitive decline has occurred such as memories starting to slip away and personality traits beginning to shift.

The team aims to make their model accessible through an app to make it accessible for patients in remote areas, potentially increasing the number of people getting screened.
 

(Except for the headline, this story has not been edited by NDTV staff and is published from a syndicated feed.)

Over 100 years ago, Alexander Graham Bell asked the readers of National Geographic to do something bold and fresh – “to found a new science.” He pointed out that sciences based on the measurements of sound and light already existed. But there was no science of odor. Bell asked his readers to “measure a smell.”

Today, smartphones in most people’s pockets provide impressive built-in capabilities based on the sciences of sound and light: voice assistants, facial recognition and photo enhancement. The science of odor does not offer anything comparable. But that situation is changing, as advances in machine olfaction, also called “digitized smell,” are finally answering Bell’s call to action.

Research on machine olfaction faces a formidable challenge due to the complexity of the human sense of smell. Whereas human vision mainly relies on receptor cells in the retina – rods and three types of cones – smell is experienced through about 400 types of receptor cells in the nose.

Machine olfaction starts with sensors that detect and identify molecules in the air. These sensors serve the same purpose as the receptors in your nose.

But to be useful to people, machine olfaction needs to go a step further. The system needs to know what a certain molecule or a set of molecules smells like to a human. For that, machine olfaction needs machine learning.

Applying machine learning to smells

Machine learning, and particularly a kind of machine learning called deep learning, is at the core of remarkable advances such as voice assistants and facial recognition apps.

Machine learning is also key to digitizing smells because it can learn to map the molecular structure of an odor-causing compound to textual odor descriptors. The machine learning model learns the words humans tend to use – for example, “sweet” and “dessert” – to describe what they experience when they encounter specific odor-causing compounds, such as vanillin.

However, machine learning needs large datasets. The web has an unimaginably huge amount of audio, image and video content that can be used to train artificial intelligence systems that recognize sounds and pictures. But machine olfaction has long faced a data shortage problem, partly because most people cannot verbally describe smells as effortlessly and recognizably as they can describe sights and sounds. Without access to web-scale datasets, researchers weren’t able to train really powerful machine learning models.

However, things started to change in 2015 when researchers launched the DREAM Olfaction Prediction Challenge. The competition released data collected by Andreas Keller and Leslie Vosshall, biologists who study olfaction, and invited teams from around the world to submit their machine learning models. The models had to predict odor labels like “sweet,” “flower” or “fruit” for odor-causing compounds based on their molecular structure.

The top performing models were published in a paper in the journal Science in 2017. A classic machine learning technique called random forest, which combines the output of multiple decision tree flow charts, turned out to be the winner.

I am a machine learning researcher with a longstanding interest in applying machine learning to chemistry and psychiatry. The DREAM challenge piqued my interest. I also felt a personal connection to olfaction. My family traces its roots to the small town of Kannauj in northern India, which is India’s perfume capital. Moreover, my father is a chemist who spent most of his career analyzing geological samples. Machine olfaction thus offered an irresistible opportunity at the intersection of perfumery, culture, chemistry and machine learning.

Progress in machine olfaction started picking up steam after the DREAM challenge concluded. During the COVID-19 pandemic, many cases of smell blindness, or anosmia, were reported. The sense of smell, which usually takes a back seat, rose in public consciousness. Additionally, a research project, the Pyrfume Project, made more and larger datasets publicly available.

Smelling deeply

By 2019, the largest datasets had grown from less than 500 molecules in the DREAM challenge to about 5,000 molecules. A Google Research team led by Alexander Wiltschko was finally able to bring the deep learning revolution to machine olfaction. Their model, based on a type of deep learning called graph neural networks, established state-of-the-art results in machine olfaction. Wiltschko is now the founder and CEO of Osmo, whose mission is “giving computers a sense of smell.”

Recently, Wiltschko and his team used a graph neural network to create a “principal odor map,” where perceptually similar odors are placed closer to each other than dissimilar ones. This was not easy: Small changes in molecular structure can lead to large changes in olfactory perception. Conversely, two molecules with very different molecular structures can nonetheless smell almost the same.

Such progress in cracking the code of smell is not only intellectually exciting but also has highly promising applications, including personalized perfumes and fragrances, better insect repellents, novel chemical sensors, early detection of disease, and more realistic augmented reality experiences. The future of machine olfaction looks bright. It also promises to smell good.

(Author:Ambuj Tewari, Professor of Statistics, University of Michigan)

(Disclosure Statement:Ambuj Tewari does not work for, consult, own shares in or receive funding from any company or organisation that would benefit from this article, and has disclosed no relevant affiliations beyond their academic appointment)

This article is republished from The Conversation under a Creative Commons license. Read the original article.
 

(Except for the headline, this story has not been edited by NDTV staff and is published from a syndicated feed.)

New Delhi:

Generative artificial intelligence (AI) which includes large language models like OpenAI’s ChatGPT, and social media can undermine efforts to address climate change, said researchers in a new forum article published in the journal Global Environmental Politics, on Friday.

Researchers from the University of British Columbia (UBC) noted that it is a common conception that AI, social media, and other tech products and platforms are either neutral or potentially net positive in their impact on climate change action.

Further, these can reduce human capacities for creative thinking and problem-solving — crucial for tackling climate change.

Additionally, the platforms also work to take away attention from pressing global issues and foster feelings of hopelessness, they said.

According to Dr Hamish van der Ven, Assistant Professor of sustainable business management of natural resources at UBC, “These technologies are influencing human behaviour and societal dynamics, shaping attitudes and responses to climate change.”

He noted that AI and social technologies can lessen our focus on the climate crisis, as they always offer “new, ever-changing content.”

Recurrent exposure to “negative news on social media may also erode optimism and increase feelings of hopelessness. All this could prevent us from organising or taking collective action on climate change,” he noted, calling for a cautious review of generative AI.

Increased dependence on these technologies may decrease the “capacity for creativity and forward-thinking solution,” noted Dr van der Ven.

Both social media and AI are also known to contribute to the spread of false or biased information — which can hobble the actions we need to take on climate change.
 

(Except for the headline, this story has not been edited by NDTV staff and is published from a syndicated feed.)

Bletchley Park, England:

China said on Wednesday it wanted to work with international partners to manage the oversight of artificial intelligence as political leaders and technology executives gathered at an inaugural AI Safety Summit in Britain to plot the way forward.

Some tech bosses and political leaders have warned the rapid development of AI poses an existential threat to the world, sparking a race by governments and international institutions to design safeguards and regulation for the future.

In a first for Western efforts to manage the safe development of AI, a Chinese vice minister joined leaders from the United States and the European Union, alongside tech bosses such as Elon Musk and ChatGPT’s Sam Altman.

“China is willing to enhance our dialogue and communication in AI safety with all sides, contributing to an international mechanism with global participation in governance framework that needs wide consensus,” Wu Zhaohui said at the start of the summit, according to an official translation of his remarks.

“Countries regardless of their size and scale have equal rights to develop and use AI,” he added.

Elon Musk, who has warned about the risks of AI, said the summit wanted to establish a “third-party referee” for companies developing the technology, so it could sound the alarm when risks develop, and so instil confidence in the public.

The meeting – held at Bletchley Park, home of Britain’s World War Two code-breakers – is the brainchild of Prime Minister Rishi Sunak. He wants to carve out a role for Britain as an intermediary between the economic blocs of the United States, China and the EU.

The summit is focused on highly capable general-purpose models called “frontier AI”

Participating governments produced a “Bletchley Declaration”, with 28 countries and the EU agreeing the need for transparency and accountability from actors in frontier AI technology, including how they will measure, monitor and mitigate potentially harmful capabilities.

A collective plan

British digital minister Michelle Donelan said it was an achievement just to get so many key players in one room.

“For the first time, we now have countries agreeing that we need to look not just independently but collectively at the risk around frontier AI,” she told reporters.

China is a key participant, given the country’s role in developing AI technology. However, some British lawmakers have questioned whether it should be there given the low level of trust between Beijing, Washington and many European capitals when it comes to Chinese involvement in technology.

The United States made clear on the eve of the summit that the call to Beijing had very much come from Britain, with its Ambassador to London, Jane Hartley, telling Reuters: “This is the UK invitation, this is not the US”.

US Vice President Kamala Harris also spoke in London on Wednesday, away from the summit, setting out her government’s response to AI, after US President Joe Biden signed an executive order on Monday.

The timing and location of her speech has raised eyebrows among some in the UK’s governing Conservative Party who suggest Washington is trying to overshadow Sunak’s summit – a charge denied by British officials who say they want as many voices as possible. Kamala Harris will meet Rishi Sunak later on Wednesday and attend the summit’s second day on Thursday.

US Secretary of Commerce Gina Raimondo used the summit to announce the launch of a US. AI Safety Institute, and said it would cooperate with Britain’s recently announced institute.

Canada’s minister of innovation, science and industry Francois-Philippe Champagne said AI would not be constrained by national borders, and therefore interoperability between different regulations being put in place was important.

“The risk is that we do too little, rather than too much, given the evolution and speed with which things are going,” he told Reuters.

On the agenda are topics like how AI systems might be used by terrorists to build bioweapons and the technology’s potential to outsmart humans and wreak havoc on the world.

(Except for the headline, this story has not been edited by NDTV staff and is published from a syndicated feed.)

New Delhi:

The Consumer Affairs Ministry today said it is working on using artificial intelligence (AI) to reduce the pendency of cases in various consumer courts in the country.

The ministry also said the National Consumer Dispute Redressal Commission (NCDRC) has successfully resolved 854 cases during August, the highest disposal rate in the current year.

This was possible due to proactive steps taken by the NCDRC, streamlined processes and advanced technology like E-daakhil, which helped resolve cases faster than ever before, it added.

“In furtherance of keeping the same momentum of disposal of cases, the Department has made filing of cases through E-daakhil in consumer commissions compulsory and soon going to launch the feature of VC (video conference) on E-daakhil,” the ministry said in a statement.

As the scope of artificial intelligence is increasing rapidly, the ministry is “also working on using the AI facilities in reducing the pendency of cases in the National, State and District Consumer Commissions,” it added.

The case filed in the Consumer Commissions will be analysed through AI and will generate the summary of the case and many more actions will be done through AI in resolving the case, the statement said.

According to the ministry, NCDRC has significantly improved the disposal of consumer cases in the commission in 2023.

NCDRC and the Department of Consumer Affairs successfully resolved 854 consumer cases in August, whereas the filing of cases during the same period was 455, making it the highest disposal rate of 188 per cent this year, it said.

This achievement underscores the NCDRC’s unwavering commitment to safeguarding consumer rights and ensuring prompt redressal of grievances, the ministry said.

Even the regular monitoring of consumer cases by the ministry and holding various one-day regional workshops in Guwahati and Chandigarh helped expedite the process.

The ministry also conducted sector-specific brainstorming sessions on insurance and real estate to reduce the pendency in the consumer commissions.

State-specific meetings in various states like Jharkhand, Madhya Pradesh, Karnataka, Rajasthan, Bihar, Maharashtra and Kerala were also held, the statement added.
 

New Delhi:

The Consumer Affairs Ministry today said it is working on using artificial intelligence (AI) to reduce the pendency of cases in various consumer courts in the country.

The ministry also said the National Consumer Dispute Redressal Commission (NCDRC) has successfully resolved 854 cases during August, the highest disposal rate in the current year.

This was possible due to proactive steps taken by the NCDRC, streamlined processes and advanced technology like E-daakhil, which helped resolve cases faster than ever before, it added.

“In furtherance of keeping the same momentum of disposal of cases, the Department has made filing of cases through E-daakhil in consumer commissions compulsory and soon going to launch the feature of VC (video conference) on E-daakhil,” the ministry said in a statement.

As the scope of artificial intelligence is increasing rapidly, the ministry is “also working on using the AI facilities in reducing the pendency of cases in the National, State and District Consumer Commissions,” it added.

The case filed in the Consumer Commissions will be analysed through AI and will generate the summary of the case and many more actions will be done through AI in resolving the case, the statement said.

According to the ministry, NCDRC has significantly improved the disposal of consumer cases in the commission in 2023.

NCDRC and the Department of Consumer Affairs successfully resolved 854 consumer cases in August, whereas the filing of cases during the same period was 455, making it the highest disposal rate of 188 per cent this year, it said.

This achievement underscores the NCDRC’s unwavering commitment to safeguarding consumer rights and ensuring prompt redressal of grievances, the ministry said.

Even the regular monitoring of consumer cases by the ministry and holding various one-day regional workshops in Guwahati and Chandigarh helped expedite the process.

The ministry also conducted sector-specific brainstorming sessions on insurance and real estate to reduce the pendency in the consumer commissions.

State-specific meetings in various states like Jharkhand, Madhya Pradesh, Karnataka, Rajasthan, Bihar, Maharashtra and Kerala were also held, the statement added.