Tag: GenAI

Most firms are limiting the use of Generative AI (GenAI) over data privacy and security issues and 27 per cent had banned its use…reports Asian Lite News

More than one in four organisations have banned the use of GenAI over privacy and data security risks, a new report showed on Monday.

Most firms are limiting the use of Generative AI (GenAI) over data privacy and security issues and 27 per cent had banned its use, at least temporarily, according to the ‘Cisco 2024 Data Privacy Benchmark Study’.

Among the top concerns, businesses cited the threats to an organisation’s legal and intellectual property rights (69 per cent), and the risk of disclosure of information to the public or competitors (68 per cent).

While 48 per cent admit entering non-public company information into GenAI tools, 91 per cent of businesses recognise they need to do more to reassure customers that their data is used for intended and legitimate purposes in AI.

About 98 per cent said that external privacy certifications are an important factor in their buying decisions, the highest level in years.

“Organisations see GenAI as a fundamentally different technology with novel challenges to consider,” said Dev Stahlkopf, Cisco Chief Legal Officer.

“More than 90 per cent of respondents believe GenAI requires new techniques to manage data and risk. This is where thoughtful governance comes into play. Preserving customer trust depends on it,” Stahlkopf added.

Most organisations are also aware of these risks and are putting in place controls to limit exposure.

About 63 per cent have established limitations on what data can be entered and 61 per cent have limits on which GenAI tools can be used by employees.

Consumers are concerned about AI use involving their data today, and yet 91 per cent of organisations recognise they need to do more to reassure their customers that their data is being used only for intended and legitimate purposes in AI.

This is similar to last year’s levels, suggesting that not much progress has been achieved, said the report.

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For LLM-based systems to reach a world-wide audience, they need to achieve the type of cultural fluency that comes instinctively to humans….reports Asian Lite News

In the coming years, culture will play a crucial role in how generative Ai is designed, deployed and consumed, Amazon CTO Dr Werner Vogels has said.

Large language models (LLMs) trained on culturally diverse data will gain a more nuanced understanding of human experience and complex societal challenges in 2024.

“This cultural fluency promises to make generative AI more accessible to users worldwide,” Vogels said during the AWS ‘re: Invent’ conference here.

For LLM-based systems to reach a world-wide audience, they need to achieve the type of cultural fluency that comes instinctively to humans.

In a paper published earlier this year, researchers from Georgia Institute of Technology demonstrated that even when an LLM was provided with a prompt in Arabic that explicitly mentioned Islamic prayer, responses were generated that recommended grabbing an alcoholic beverage with friends, which isn’t culturally appropriate.

According to Vogels, a lot of this has to do with the training data that’s available.

“Common Crawl, which has been used to train many LLMs, is roughly 46 per cent English, and an even greater percentage of the content available — regardless of language — is culturally Western (skewing significantly towards the United States),” he noted.

In the past few months, non-Western LLMs have started to emerge: Jais, trained on Arabic and English data, Yi-34B, a bilingual Chinese/English model, and Japanese-large-lm, trained on an extensive Japanese web corpus.

“These are signs that culturally accurate non-Western models will open up generative AI to hundreds of millions of people with impacts ranging far and wide, from education to medical care,” the Amazon CTO emphasised.

Just as humans learn from discussion, debate, and the exchange of ideas, LLMs need similar opportunities to expand their perspectives and understand culture.

According to him, two areas of research will play a pivotal role in this cultural exchange.

One is reinforcement learning from AI feedback (RLAIF), in which a model incorporates feedback from another model.

In this scenario, different models can interact with each other and update their own understandings of different cultural concepts based on these interactions.

“Second is collaboration through multi-agent debate, in which multiple instances of a model generate responses, debate the validity of each response and the reasoning behind it, and finally come to an agreed upon answer through this debate process. Both areas of research reduce the human cost it takes to train and fine-tune models,” Vogels noted.

As LLMs interact and learn from each other, they will gain more nuanced understandings of complex societal challenges informed by diverse cultural lenses, he added.

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This is more than twice the rate of growth in overall AI spending and almost 13 times greater than the CAGR for worldwide IT spending over the same period….reports Asian Lite News

Global spending on generative AI (GenAI) software and solutions is expected to reach $143 billion in 2027 with a compound annual growth rate (CAGR) of 73.3 per cent, according to a new report.

This is more than twice the rate of growth in overall AI spending and almost 13 times greater than the CAGR for worldwide IT spending over the same period.

The forecast from International Data Corporation (IDC) shows that enterprises will invest nearly $16 billion worldwide on GenAI solutions in 2023.

This spending includes GenAI software as well as related infrastructure hardware and IT/business services.

“Generative AI is more than a fleeting trend or mere hype. It is a transformative technology with far-reaching implications and business impact,” says Ritu Jyoti, group vice president, worldwide AI and automation market research and advisory services.

With ethical and responsible implementation, GenAI is poised to reshape industries, changing the way we work, play, and interact with the world,” she added.

IDC expects GenAI investments to follow a natural progression over the next several years as organisations transition from early experimentation to aggressive build out with targeted use cases to widespread adoption across business activities.

“The rate of GenAI spending will be somewhat constrained through 2025 due to turbulence in workload shifts and resource allocation, not just in silicon but also in networking, facilities, model confidence, and AI skills,” said Rick Villars, group vice president, worldwide research at IDC.

By the end of the forecast period, GenAI spending will account for 28.1 per cent of overall AI spending, up significantly from 9 per cent in 2023. “GenAI infrastructure, including hardware, Infrastructure as a Service (IaaS), and system infrastructure software (SIS), will represent the largest area of investment during the build out phase,” the report noted.

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To adapt and empower the workforce with the necessary skills and tools, Coforge has proactively developed internal learning paths and curriculum…writes Nishant Arora

As generative AI (aka chatbots) spark a lot of debate among its stakeholders, industry leaders in India believe that while there are some risks associated primarily related to data, privacy and security, generative AI has more opportunities than risks and we are yet to explore its true potential to improve productivity, ingenuity, creativity, efficiency, and communication.

Generative AI refers to algorithms that have the capability to create original content, including text, images, videos, or audio.

“Generative AI (GenAI), specifically around large language models (LLMs) has lately garnered a lot of interest and sparked a lot of discussion in the community.  GenAI is an assistive and augmented technology when used by humans, it can add to the creativity and ingenuity of humans,” Vic Gupta, Chief Technology Officer, Coforge, told IANS.

To adapt and empower the workforce with the necessary skills and tools, Coforge has proactively developed internal learning paths and curriculum.

“To demonstrate our preparedness and effectiveness in various industries and across different use cases, we have identified over 100 potential scenarios, use cases and solutions that solve one or more client business problems,” Gupta informed.

The company has also partnered with Microsoft as their investments in OpenAI align perfectly with its goals.

“We have already integrated the public OpenAI into our Quasar, an Intelligent AI Platform, allowing us to utilise ChatGPT APIs for tasks such as data summarisation, classification, and segmentation,” said Gupta.

While ChatGPT has gained significant attention recently, it’s important to understand that generative AI encompasses much more than just ChatGPT.

“For instance, when you pose a question to ChatGPT and receive an answer, the algorithm generates the text of the response based on its learning from a vast amount of training data. Similarly, other generative AI algorithms like DALL-E can generate images based on text prompts given to them,” said Anil Kaul, Chief AI Officer, Infogain.

GenAI has many potential applications. For example, a portfolio manager at a bank could use GenAI to generate investment advice.

“In customer relationship management (CRM) systems, GenAI can summarise conversation transcripts and extract pending action items that the customer support team can follow up on. In technical support, GenAI plays an important role in finding resolutions to myriad issues in a quick and effective manner,”  Prabhakar Srinivasan, Director of Technology, AI/ML/Data Science at Synechron, told IANS.

In cybersecurity or finance, generative models can learn what normal transactions or network traffic look like and generate alarms when anomalies occur.

“GenAI can also generate code which can be a productivity boost for developers. In all these examples of applications, GenAI augments the capabilities of human experts and hence plays the role of co-pilot,” Srinivasan informed.

While generative AI has its perks, one key issue faced by users is Artificial Intelligence hallucinations.

When we feed in a question and the systems don’t understand the question or it’s misinterpreted, the system generates a response regardless, with incorrect information. Something that doesn’t actually exist.

“Added to this, its data-driven algorithms limit the system’s information pool. The systems struggle with understanding context, especially when presented with new or unfamiliar information or scenarios. It lacks creativity and tends to miss nuances while creating content- which can be fixed with human touch,” informed Jacob Joseph, VP–Data Science, CleverTap.

According to Srinivasan, relying heavily on generative AI without the necessary checks and balances from a human expert to validate the results can lead to potentially unsafe and/or unethical or biased applications.

“Guardrails must be put into place due to legal and ethical issues around copyrights and attribution of source. There are also some risks on how people will use them, creating deep-fakes or generating fake news,” he noted.

Even in its most basic form, ChatGPT could be deployed as a more advanced customer support chatbot.

“We have already seen glimpses of this with Intercom announcing ‘Fin’, a GPT-4 powered customer service chatbot that requires zero setups and understands complicated support tickets without human intervention. Furthermore, some generative AI tools enable brands to create more personalised and emotionally resonant campaigns, helping brands,” Joseph emphasised.

Generative AI, hailed as the ‘next big thing’ in MarketingTech (MarTech), holds the potential to elevate marketers to ’10x marketer’ status.

“By delving into the intricacies of generative AI, marketers can unlock a realm of new possibilities. Integrating generative AI into various workflows, even those that are siloed, has the power to address long-standing challenges in MarTech, such as scaling hyper-personalized content,” he added.

While a lot of companies are only still experimenting with the technology, pricing is not going to be a game changer for the adoption of generative AI tools.

“Seeing how it unlocks unprecedented levels of productivity and innovation, businesses are going to be open to investing in the technology,” Joseph said.

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