Google’s Generative AI Models Face Privacy Risk Assessment in Europe

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TheGen.AI News

Google’s Generative AI Models Face Privacy Risk Assessment in Europe

The European Union's lead privacy regulator for Google has initiated an investigation into whether the company adhered to the bloc's data protection laws when using personal data to train its generative AI models. The focus is on whether Google should have conducted a Data Protection Impact Assessment (DPIA) to evaluate potential risks its AI technologies could pose to individuals' rights and freedoms. Generative AI tools, which can produce misleading information and personal details, create significant legal risks. Ireland's Data Protection Commission (DPC), responsible for ensuring Google's compliance with the General Data Protection Regulation (GDPR), can impose fines of up to 4% of Alphabet’s global turnover for violations.

Google’s AI tools, such as its Gemini-branded large language models (LLMs), are being scrutinized, particularly the PaLM2 model, which supports various AI applications, including chatbots and enhanced search features. The DPC is investigating the methods used to develop PaLM2 under Section 110 of Ireland’s Data Protection Act, which incorporates the GDPR.

Generative AI models require vast data sets for training, raising concerns about how and where companies like Google acquire personal information, especially within the EU's stringent privacy regulations. The DPC’s investigation is part of broader scrutiny of AI privacy compliance, with companies like OpenAI and Meta already facing similar questions. Elon Musk’s X has also been under investigation for its use of data in AI training.

The DPC’s inquiry into Google’s compliance with Article 35 of the GDPR, which mandates DPIAs for high-risk data processing, is the latest regulatory action in this area. The DPC emphasized the importance of DPIAs in safeguarding individuals’ fundamental rights when high-risk data processing is involved. Google declined to comment on the sources of its training data but expressed willingness to cooperate with the DPC in a statement.

CSDI Report Warns of Gen AI’s Role in Spreading Misinformation During Elections

Artificial Intelligence (AI) has influenced many aspects of human life and has now progressed beyond concerns about job losses to a new area of concern. The growing presence of generative AI has raised significant worries about its potential global impact on democratic processes like elections.

A report from the Centre for the Study of Democratic Institutions (CSDI), a Canadian think tank, titled “Harmful Hallucinations: Generative AI and Elections,” delves into the risks generative AI poses to election integrity. The report, authored by Chris Tenove, Nishtha Gupta, and Netheena Mathews, among others, highlights both the risks and opportunities of generative AI in elections.

The year 2024 has been labeled the era of "Deepfake Elections" due to numerous incidents involving AI technologies in campaigns across the US, India, and the European Union. While generative AI is not entirely new, its growing accessibility and advancements have made it easier to produce deceptive content, such as AI-generated misinformation, manipulated media, and deepfakes.

"Generative AI technologies lower the cost of producing deceptive content, amplifying existing threats to democracy," said Chris Tenove, assistant director of CSDI. He noted that AI has magnified pre-existing problems rather than creating entirely new ones.

CSDI has studied how different technologies affect democratic institutions for years. With elections in the US, India, Brazil, and other nations taking place in 2024, the research team sought to examine the potential harmful uses of generative AI in these elections.

“There’s a lot of hype and concern surrounding the impact of generative AI on politics and elections. We wanted to gather real evidence on how it might be misused and its potential impact, as well as identify solutions to counter those threats,” Tenove explained to indianexpress.com.

The report classifies the risks of generative AI into three main areas: deception, harassment, and pollution of information environments. Through real-world examples, it shows how generative AI can mislead voters, harass political candidates, or overwhelm the public with low-quality, inaccurate content.

SAP Study Reveals 96% of Indian Midmarket Firms Are Prioritizing Generative AI

A recent SAP study reveals that an impressive 96% of midmarket businesses in India are prioritizing generative artificial intelligence (Gen AI), surpassing the global average of 91%. This insight was presented at SAP Now, the company’s flagship event in Delhi on September 13, 2024. The research, which surveyed over 12,000 businesses globally, including 800 in India, highlights the swift adoption of AI by Indian businesses as they strive to remain competitive in a digital-first landscape.

Midmarket businesses in India, defined as those with 250 to 1,500 employees, are increasingly recognizing the transformative power of Gen AI. The study found that 96% of these companies view Gen AI as either a moderate or strong priority, a figure higher than the global average, underscoring India’s focus on harnessing AI for growth and innovation.

In 2024, 66% of Indian midmarket companies rank the adoption of Gen AI as a top priority, second only to preparing for cybersecurity threats (67%), and ahead of initiatives to improve environmental sustainability (65%). This reflects a broader strategy to integrate AI into core business functions to enhance efficiency, agility, and real-time decision-making.

The study also indicates that Indian midmarket businesses are prioritizing AI to improve key areas such as privacy and security (55%) and decision-making (52%), figures that are notably higher than in other regions. Additionally, Indian companies are leveraging AI to boost training and skills development (51%), enhance customer experience (50%), and optimize supply chains (50%). Early adopters like PGP Glass and Suzlon Energy are already using AI to gain a competitive edge in their industries.

TheOpensource.AI News

Open-Source Communities Key to Developing Safe and Responsible AI, Say Experts

As global efforts to develop artificial general intelligence (AGI) continue, true adoption will only occur when AGI is accepted by all stakeholders—requiring it to be explainable, stable, and reliable, according to tech leaders on Thursday. AI is becoming a critical factor in determining the economic success of nations, and India, as a founding member of the Global Partnership on Artificial Intelligence (GPAI), has been part of this initiative since June 2020.

A new initiative is set to accelerate the AGI landscape with the formation of a collaborative group focused on building safe super intelligence (SSI). This invite-only group aims to bring together a diverse range of academicians, developers, startups, enterprises, and venture capitalists (VCs) to collaborate on shaping the future of safe AGI worldwide.

Vinay Kumar Sankarapu, CEO and Founder of Arya.ai and a well-known figure in the AI community, stated that the goal is to establish and expand an open-source research community that can crowdsource solutions to multiple critical challenges, "laying the groundwork for achieving safe super intelligence."

The SSI group will dedicate two-thirds of its efforts to research and one-third to applied machine learning, with a presence in the US, India, Singapore, and the UK. The initiative's objective is to foster collaboration among businesses, academia, VCs, and developers to build a sustainable SSI ecosystem.

This SSI Club initiative is led by AI innovator and IIT Bombay graduate Sankarapu, who was also a member of the Commerce and Industry Minister Nirmala Sitharaman’s 'Task Force on Artificial Intelligence for Economic Transformation' in 2017.

The initiative is a joint collaboration between Arya.ai, Nayyan Mujadiya (organizer of FutureGPT and lead member at Siemens EDA), and Nikhil Agarwal (co-organizer of FutureGPT and product security architect at Ethos and cybersecurity consultant).

Founded in 2013, Arya.ai was one of the first AI startups to apply deep learning and integrate it into enterprise solutions.

Open Source AI Positioned to Lead the Future of Technological Innovation

Reporting from the Red Hat Summit in Johannesburg, Kathy Gibson notes that artificial intelligence (AI) has become a prominent focus in the IT industry over the past year, positioning itself as a mainstream technology capable of addressing organizational IT and business challenges.

Dion Harvey, regional GM of Red Hat Sub-Saharan Africa, highlights that 2024 has been a year of rapid innovation, with the pace only set to increase. He emphasizes that although the industry is experiencing constant disruption, such as through cloud computing and virtualization, this upheaval brings opportunities.

Hans Roth, Red Hat’s senior vice president and GM for EMEA, adds that businesses worldwide are exploring AI innovations, and as a leader in open-source technology, Red Hat is committed to enabling the open-source community to contribute to AI’s development. Roth believes AI represents the next major open-source revolution.

Red Hat has been instrumental in making various technologies more accessible to customers through open-source collaboration. However, businesses still face challenges when implementing AI, particularly in complex environments with multi-cloud, on-premises, and edge-based applications. Roth underscores the importance of secure, automated infrastructure that can run any application and of fostering collaboration within teams.

Recently, Red Hat announced its expansion of the Open Hybrid Cloud, integrating AI across its portfolio. The updated platform elevates automation to a critical function and provides tools to increase developer productivity, with a focus on delivering AI in secure, trusted environments.

According to Roth, AI has driven innovation for the past decade, and there is more to come, especially with the emergence of generative AI (GenAI). Brian Gracely, senior director of portfolio strategy at Red Hat, agrees, noting that while AI isn’t new, it now feels accessible for experimentation.

Gracely emphasizes the critical role of open-source technology in AI’s rollout, explaining how open technologies have driven past IT revolutions, including private, public, and hybrid cloud adoption. AI continues to evolve quickly, and the market has become more open over the past year. However, Gracely acknowledges there is still much to be done, and Red Hat is committed to making AI even more open through collaboration.

As part of this effort, Red Hat has been involved in developing open-source AI models, partnering with IBM Research to release the Granite models on platforms like HuggingFace and GitHub. Gracely also questions the trend toward ever-larger AI models, suggesting that smaller models may often be more efficient and cost-effective for businesses.

A major challenge for companies is the cost of running AI, which can be prohibitive. To address this, Red Hat introduced InstructLab, a toolset designed to simplify model creation for subject matter experts, allowing businesses to take control of their own AI while maintaining security over their data.

Earlier this year, Red Hat launched a comprehensive AI portfolio on Open Hybrid Cloud platforms, including AI models on Red Hat Enterprise Linux (RHEL) AI, OpenShift AI, Lightspeed, and AI workloads. Gracely believes this portfolio provides customers with trust, choice, and consistency in their AI efforts.

Privacera Unveils PAIG Open-Source Framework for Secure, Ethical AI

Privacera, a company specializing in AI and data security governance founded by the creators of Apache Ranger, has announced the open-sourcing of its Privacera AI Governance (PAIG) solution. The open-source platform, called PAIG Open-Source Software (PAIG OSS), empowers developers to build innovative Generative AI (GenAI) applications while maintaining strong ethics, privacy, and security standards.

The rapid adoption of GenAI has surpassed expectations, with 10% of Global 2000 companies already implementing GenAI projects. However, the risks of using AI in applications that manage sensitive corporate or personal data are becoming increasingly evident.

Larger companies are advised to test complete solutions before fully committing to GenAI, as retrofitting security and governance can be problematic. Meanwhile, smaller organizations require a simpler way to protect sensitive data. PAIG OSS offers an open-source toolkit that supports organizations of all sizes in creating secure GenAI solutions.

Balaji Ganesan, CEO and Co-Founder of Privacera, emphasized the importance of open-source frameworks like PAIG OSS in shaping the future of GenAI. He noted that such frameworks encourage transparency, collaboration, and inclusivity, which are vital for accelerating innovation while ensuring ethical AI development. Ganesan also highlighted the role of API governance and data leadership in building trust in AI systems.

Jiang Chen, Head of Ecosystem and Developer Relations at Zilliz, explained that PAIG OSS offers security features for GenAI applications, allowing developers to innovate without sacrificing safety. It integrates fine-grained access control through the Milvus vector database, ensuring sensitive data stays secure while maintaining high performance.

A study by the IBM Institute for Business Value found that only 24% of current AI projects include security components, even though 82% of executives believe that secure and trustworthy AI is critical to business success.

To address this need, Privacera’s PAIG.ai initiative, which provides security measures for GenAI applications, was featured at IBM's TechXchange Conference 2024 during Open-Source Community Day, attracting more than 8,000 developers.

TheClosedsource.AI News

Chai Discovery Unveils AI Model Chai-1 with OpenAI's Support for Advancing Drug Research

Artificial Intelligence is advancing rapidly across various sectors. Recently, OpenAI and venture capital firm Thrive Capital announced their support for Chai Discovery, a biology startup founded by former researchers from OpenAI and Meta. The startup raised nearly $30 million to develop AI models for drug discovery.

On September 9, Chai Discovery introduced Chai-1, an advanced AI model designed to predict molecular structures, which are crucial for drug discovery. The company has made the model accessible for free via a web interface and is also sharing the code and tools for non-commercial purposes to encourage further research and development.

What is Chai’s AI model Chai-1? Chai-1 can predict the structure of biochemical molecules, potentially accelerating drug development. According to the developers, Chai-1 surpasses Google DeepMind’s AlphaFold on certain benchmarks. It works with various types of molecules, including small molecules, proteins, DNA, RNA, and chemical modifications. The model is free and open-source, encouraging research and innovation.

A detailed analysis of Chai-1 is available in the Chai-1 Technical Report. The report highlights the model's exceptional performance in predicting how proteins, small molecules, and drugs interact. Chai-1 handles multiple tasks with ease, such as predicting interactions between different proteins.

Real-world applications Chai-1 can handle diverse inputs like raw molecular data, experimental results, and sequence information, making it especially useful in real-world scenarios where data is incomplete. Unlike other models, it does not require Multiple Sequence Alignments (MSAs) to deliver accurate results.

Chai-1 excels across various benchmarks, outperforming Google DeepMind’s AlphaFold3 in tasks like predicting protein-ligand interactions. The model is designed for practical use in research and drug discovery, offering a cutting-edge tool for understanding biological molecule structures, with significant potential in pharmaceuticals.

While Google DeepMind’s AlphaFold remains the most advanced protein prediction model, Chai-1's superior performance in certain areas signals rapid AI progress. With major investments pouring into AI-driven drug discovery, we may be approaching breakthroughs in curing major diseases.

Tiger Global Set to Join OpenAI's Multi-Billion-Dollar Funding Round: Report

Venture capital firm Tiger Global Management is set to participate in a multi-billion-dollar funding round for OpenAI, potentially valuing the ChatGPT developer at $150 billion, according to a report by the Information on Friday, citing sources familiar with the situation.

OpenAI's rapid rise in popularity has fueled significant interest in generative AI, with companies rushing to incorporate the technology into their products. Tiger Global would join a group of high-profile investors, including Thrive Capital, Microsoft, Nvidia, Apple, Abu Dhabi-based AI investment firm G42, and Khosla Ventures, who are also reportedly in discussions to join the funding round.

Thrive Capital, led by Josh Kushner, plans to commit $1 billion and is expected to lead the round, according to the report.

The Sam Altman-led AI startup is raising $6.5 billion from investors and is also seeking an additional $5 billion in debt through a revolving credit facility from banks, Bloomberg News reported on Thursday. Both OpenAI and Tiger Global Management did not immediately respond to Reuters' requests for comment.

OpenAI recently introduced its "Strawberry" series of AI models, which are designed to spend more time processing responses to address complex problems.

Zoho Analytics Launches with Self-Service BI and OpenAI Integration

Zoho has introduced an updated version of its self-service BI and analytics platform, Zoho Analytics, featuring over 100 enhancements with a focus on artificial intelligence (AI) and machine learning (ML). A key highlight of the update is the seamless integration with OpenAI, enabling businesses to gain deeper insights and make informed, data-driven decisions.

Clarence Rozario, Director of Product Management for Zoho BI & Analytics, discussed the innovations and impacts of the release.

Generative AI at the Core One of the standout updates is the integration of Generative AI, allowing users to interact with data through conversational and visual methods. As Clarence explains, "You can ask a question like 'order quality by shipboard and by order time,' and it generates a helpful chart as a response." This feature lowers the barrier for users without deep data science knowledge, making advanced analytics easier to access. Future multilingual support will allow users to engage in languages like French and Spanish, further enhancing accessibility. The platform also integrates with Microsoft Teams, enabling users to interact with the BI system directly in their workspace. Clarence highlights the growing user-centric focus, saying, "We are bringing intelligence to where people work."

AI-Driven Insights for Non-Technical Users Zoho Analytics also introduces features aimed at non-technical users, including OpenAI integration. This provides an intelligent assistant that helps users build SQL queries, suggest formulas, and find public datasets. Clarence elaborates, "You can ask OpenAI for a formula to calculate year-to-date average sales, and it will suggest one." This feature makes advanced data manipulation more accessible to a wider range of users, bridging the gap between business professionals and data scientists. Additionally, the integration employs Retrieval Augmented Generation (RAG) technology to improve the accuracy of large language model outputs, reducing errors and providing more reliable insights. As Clarence explains, "We use RAG technology to ensure the OpenAI results are more accurate and reduce hallucinations."

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