In an interview at the recent AI & Big Data Expo, Streambased founder and CEO Tom Scott outlined the company’s approach to enabling advanced analytics on streaming data. At the foundation of Streambased’s offering is Apache Kafka, an open-source event streaming platform that has been widely adopted by Fortune 500 companies.

“Where [Kafka] falls down is in large-scale analytics,” explained Scott. While Kafka reliably transports high-volume data streams between applications and microservices, conducting complex analytical workloads directly on streaming data has historically been challenging. 

Streambased adds a proprietary acceleration technology layer on top of Kafka that makes the platform suitable for the type of demanding analytics use cases data scientists and other analysts want to perform.

Because these continuously flowing event streams power critical operational systems and core business functions, data quality must already meet high standards in terms of accuracy, timeliness, and structure. By leveraging these existing Kafka data pipelines, Streambased ensures its analytical capabilities have access to up-to-date, clean and well-organised data.

Use cases that showcase the power of Streambased’s approach include fraud detection in financial services. If an anomalous transaction occurs, analysts can quickly query similar or related transactions to investigate – which would be difficult and inefficient to accomplish with a pure streaming architecture. Streambased’s optimization for analytical interactivity enables users to rapidly gather contextual insights without disrupting their workflow.

The convergence of operational and analytical data platforms represents an impactful trend that Streambased calls the “streaming data lake” movement

“I think we are at the period of the streaming data lake movement. And by a streaming data lake, I mean a complete convergence between data systems that we use for analytical purposes and data systems that we use for operational purposes,” explains Scott.

Recent enhancements like infinite data retention in Kafka and native streaming analytics services lay the foundation for this new paradigm. For now, Streambased remains focused on empowering business analysts through frictionless self-service access to granular real-time data, without requiring changes to existing tools and processes.

You can watch our full interview with Tom Scott below:

(Photo by Robert Zunikoff on Unsplash)

See also: AI & Big Data Expo: Unlocking the potential of AI on edge devices

Want to learn more about AI and big data from industry leaders? Check out AI & Big Data Expo taking place in Amsterdam, California, and London. The comprehensive event is co-located with Cyber Security & Cloud Expo and Digital Transformation Week.

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Zheng first explained how over a decade working in digital marketing and e-commerce sparked her interest more recently in data analytics and artificial intelligence as machine learning has become hugely popular.

At Canon, Zheng’s team focuses on ethically integrating AI into business by first mapping current and potential AI applications across areas like marketing and e-commerce. They then analyse and assess risks to ensure compliance with regulations.

Canon is actively mapping out AI applications and assessing risks, as Grace explained, “to align with regulations such as the EU legislations.”

As founder of Kosh Duo, Zheng also provides coaching to help businesses scale up through the use of AI marketing and data-driven approaches. She coaches professionals on achieving greater recognition and rewards by leveraging AI tools as well.

A key challenge she encounters is misunderstandings around what AI truly means – many conflate it solely with chatbots like ChatGPT rather than appreciating the full breadth of machine learning, neural networks, natural language processing, and more that enable today’s AI.

“There’s a lot of misconceptions, definitely. One of the biggest fears, as I touched on, is the very generic understanding that GPT equals AI,” says Zheng. “[Kosh Duo] provides coaching services to businesses to scale to the next level using AI marketing and data-driven approaches.”

When asked about trends to watch, Zheng emphasised the need for continual learning given how rapidly the field evolves. She expects that 2024 will be an “awakening year” where businesses truly grasp AI’s potential and individuals appreciate the need to evaluate their current skillsets.

The interview highlighted the transformative but often misunderstood power of AI in business and the importance of developing specialised skills to properly harness it. Zheng stressed that with the right ethical foundations and coaching, AI and machine learning can become positive forces to drive growth rather than something to fear.

Watch our full interview with Grace Zheng below:

(Photo by Benjamin Davies on Unsplash)

Want to learn more about AI and big data from industry leaders? Check out AI & Big Data Expo taking place in Amsterdam, California, and London. The comprehensive event is co-located with Cyber Security & Cloud Expo and Digital Transformation Week.

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Available for Vertex AI customers on the allowlist, Imagen 2 enables users to craft and deploy photorealistic images using intuitive tooling and fully-managed infrastructure. 

Developed with Google DeepMind technology, Imagen 2 offers improved image quality and a range of functionalities tailored for specific use cases.

Key features of Imagen 2 include:

• Diverse image generation: Imagen 2 excels in creating high-resolution images from natural language prompts that cater to various user requirements.

• Text rendering in multiple languages: Overcoming common challenges, Imagen 2 supports accurate text rendering in multiple languages.

• Logo generation: Businesses can leverage Imagen 2 to create a variety of creative and realistic logos—with the option to overlay them on products, clothing, business cards, and more.

• Captions and question-answering: Imagen 2’s advanced image understanding capabilities facilitate the creation of descriptive captions and provide detailed answers to questions about image elements.

• Multi-language support: Imagen 2 introduces support for six additional languages in preview, with plans for more in early 2024. This includes the ability to translate between prompt and output.

• Safety measures: Imagen 2 incorporates built-in safety precautions, aligning with Google’s Responsible AI principles. It features safety filters and integrates with a digital watermarking service to ensure responsible use.

Enterprise-ready capabilities

Imagen 2 on Vertex AI is designed to meet enterprise standards, offering reliability and governance akin to its predecessor. With new features such as high-quality image rendering, improved text rendering, logo generation, and safety measures, Imagen 2 aims to provide organisations with a comprehensive tool for creative image generation.

Leading companies like Snap, Shutterstock, and Canva have already embraced Imagen for creative purposes.

Chris Loy, Director of AI Services at Shutterstock, commented: “We exist to empower the world to tell their stories by bridging the gap between idea and execution.

“Variety is critical for the creative process, which is why we continue to integrate the latest and greatest technology into our image generator and editing features—as long as it is built on responsibly sourced data,”

Danny Wu, Head of AI at Canva, added: “We’re continuing to use generative AI to innovate the design process and augment imagination.

“With Imagen, our 170M+ monthly users can benefit from the image quality improvements to uplevel their content creation at scale.”

As Imagen 2 makes waves in the creative industry, organisations are encouraged to explore its potential. Google Cloud anticipates users will harness the new features to elevate their creative endeavours and build on the success achieved with Imagen.

(Photo by G on Unsplash)

See also: Microsoft unveils 2.7B parameter language model Phi-2

Want to learn more about AI and big data from industry leaders? Check out AI & Big Data Expo taking place in Amsterdam, California, and London. The comprehensive event is co-located with Digital Transformation Week.

Explore other upcoming enterprise technology events and webinars powered by TechForge here.

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The report underscores the need for a composite AI approach. This involves combining various AI types – such as generative, predictive, and causal – along with diverse data sources like observability, security, and business events. This holistic strategy aims to provide precision, context, and meaning to AI outputs, ensuring reliable results.

Key findings:

• 83% of tech leaders emphasise the mandatory role of AI in navigating the dynamic nature of cloud environments.
• 82% anticipate AI’s critical role in security threat detection, investigation, and response.
• 88% foresee AI extending access to data analytics for non-technical employees through natural language queries.
• 88% believe AI will enhance cloud cost efficiencies through support for Financial Operations (FinOps) practices.

“AI has become central to how organisations drive efficiency, improve productivity, and accelerate innovation,” said Bernd Greifeneder, Chief Technology Officer at Dynatrace.

“The release of ChatGPT late last year triggered a significant generative AI hype cycle. Business, development, operations, and security leaders have set high expectations for generative AIs to help them deliver new services with less effort and at record speeds.”

While organisations express optimism about AI’s transformative potential, concerns linger:

• 93% of tech leaders worry about potential non-approved uses of AI as employees become more accustomed to tools like ChatGPT.
• 95% express concerns about using generative AI for code generation, fearing leakage and improper use of intellectual property.
• 98% are apprehensive about unintentional bias, errors, and misinformation in generative AI.

“Especially for use cases that involve automation and depend on data context, taking a composite approach to AI is critical. For instance, automating software services, resolving security vulnerabilities, predicting maintenance needs, and analysing business data all need a composite AI approach,” added Greifeneder.

“This approach should deliver the precision of causal AI, which determines the underlying causes and effects of systems’ behaviours, and predictive AI, which forecasts future events based on historical data.”

As organisations forge ahead with AI adoption, balancing enthusiasm with a mindful approach to challenges becomes paramount. The survey underscores the transformative potential of AI, but its effective integration requires careful consideration and a diversified AI strategy.

“Predictive AI and causal AI not only provide essential context for responses produced by generative AI but can also prompt generative AI to ensure precise, non-probabilistic answers are embedded into its response,” says Greifeneder.

“If organisations get their strategy right, combining these different types of AI with high-quality observability, security, and business events data can significantly boost the productivity of their development, operations, and security teams and deliver lasting business value.”

A full copy of the report can be found here (registration required)

(Photo by Matt Sclarandis on Unsplash)

See also: AI & Big Data Expo: Demystifying AI and seeing past the hype

Want to learn more about AI and big data from industry leaders? Check out AI & Big Data Expo taking place in Amsterdam, California, and London. The comprehensive event is co-located with Cyber Security & Cloud Expo and Digital Transformation Week.

Explore other upcoming enterprise technology events and webinars powered by TechForge here.

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Craven — with an extensive background in engineering and leadership roles at McKinsey & Company, HSBC, Nokia, among others — shared his experiences as a consultant helping C-level executives navigate the complex landscape of AI adoption. The core message revolved around understanding AI beyond the hype to make informed decisions that align with organisational goals.

Breaking down the AI hype

Craven introduced a systematic approach to demystifying AI, emphasising the need to break down the overarching concept into smaller, manageable components. He outlined key attributes of neural networks, embeddings, and transformers, focusing on large language models as a shared foundation.

• Neural networks — described as probabilistic and adaptable — form the backbone of AI, mimicking human learning processes.
• Embeddings allow computers to navigate between levels of abstraction, somewhat akin to human cognition.
• Transformers — the “attention” mechanism — are the linchpin of the AI revolution, allowing machines to understand context and meaning.

LLMs as search and research engines

Craven assesses if LLMs alone make good search engines. They understand search intent exceptionally well but don’t have access to vast data, give accurate results, or reference sources—all of which are key search requirements.

However, Craven highlighted that large language models (LLMs) are powerful summarising engines for research. He emphasised their ability to summarise data, translate between languages, and serve as research assistants:

Craven went on to caution against relying solely on LLMs for complex tasks—showcasing a study where consultants using language models underperformed in nuanced analysis.

De-hyping AI: Setting realistic expectations

The presentation concluded with practical use cases for organisations, such as documentation tools, high-level decision-making, code review tools, and multimodal decision-makers. Craven advised a thoughtful evaluation of when LLMs are useful, ensuring they align with organisational values and principles.

However, Craven warns against inflated claims about AI’s performance—citing examples where language models enhanced certain tasks but fell short in others. He urged the audience to consider the context and nuances when evaluating AI’s impact, avoiding unwarranted expectations.

Craven offered actionable insights for implementation, urging organisations to capture data for future use, create test cases for specific use cases, and apply a systematic framework to develop a strategy. The emphasis remained on seeing through the hype, saving millions by strategically incorporating AI into existing workflows.

In a world inundated with AI promises, Adam Craven’s pragmatic approach provides a roadmap for organisations to leverage the power of AI while avoiding common pitfalls.

Want to learn more about AI and big data from industry leaders? Check out AI & Big Data Expo taking place in Amsterdam, California, and London. The comprehensive event is co-located with Cyber Security & Cloud Expo and Digital Transformation Week.

Explore other upcoming enterprise technology events and webinars powered by TechForge here.

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Paul O’Sullivan, Senior Vice President of Solution Engineering (UKI) at Salesforce, sheds light on the complexities of this transformative landscape, urging businesses to tread cautiously while embracing the potential of artificial intelligence.

Unprecedented opportunities

Generative AI has stormed the scene with remarkable speed. ChatGPT, for example, amassed 100 million users in a mere two months.

“If you put that into context, it took 10 years to reach 100 million users on Netflix,” says O’Sullivan.

This rapid adoption signals a seismic shift, promising substantial economic growth. O’Sullivan estimates that generative AI has the potential to contribute a staggering £3.5 trillion ($4.4 trillion) to the global economy.

“Again, if you put that into context, that’s about as much tax as the entire US takes in,” adds O’Sullivan.

One of its key advantages lies in driving automation, with the prospect of automating up to 40 percent of the average workday—leading to significant productivity gains for businesses.

The AI trust gap

However, amid the excitement, there looms a significant challenge: the AI trust gap. 

O’Sullivan acknowledges that despite being a top priority for C-suite executives, over half of customers remain sceptical about the safety and security of AI applications.

Addressing this gap will require a multi-faceted approach including grappling with issues related to data quality and ensuring that AI systems are built on reliable, unbiased, and representative datasets. 

“Companies have struggled with data quality and data hygiene. So that’s a key area of focus,” explains O’Sullivan.

Safeguarding data privacy is also paramount, with stringent measures needed to prevent the misuse of sensitive customer information.

“Both customers and businesses are worried about data privacy—we can’t let large language models store and learn from sensitive customer data,” says O’Sullivan. “Over half of customers and their customers don’t believe AI is safe and secure today.”

Ethical considerations

AI also prompts ethical considerations. Concerns about hallucinations – where AI systems generate inaccurate or misleading information – must be addressed meticulously.

Businesses must confront biases and toxicities embedded in AI algorithms, ensuring fairness and inclusivity. Striking a balance between innovation and ethical responsibility is pivotal to gaining customer trust.

“A trustworthy AI should consistently meet expectations, adhere to commitments, and create a sense of dependability within the organisation,” explains O’Sullivan. “It’s crucial to address the limitations and the potential risks. We’ve got to be open here and lead with integrity.”

As businesses embrace AI, upskilling the workforce will also be imperative.

O’Sullivan advocates for a proactive approach, encouraging employees to master the art of prompt writing. Crafting effective prompts is vital, enabling faster and more accurate interactions with AI systems and enhancing productivity across various tasks.

Moreover, understanding AI lingo is essential to foster open conversations and enable informed decision-making within organisations.

A collaborative future

Crucially, O’Sullivan emphasises a collaborative future where AI serves as a co-pilot rather than a replacement for human expertise.

“AI, for now, lacks cognitive capability like empathy, reasoning, emotional intelligence, and ethics—and these are absolutely critical business skills that humans need to bring to the table,” says O’Sullivan.

This collaboration fosters a sense of trust, as humans act as a check and balance to ensure the responsible use of AI technology.

By addressing the AI trust gap, upskilling the workforce, and fostering a harmonious collaboration between humans and AI, businesses can harness the full potential of generative AI while building trust and confidence among customers.

You can watch our full interview with Paul O’Sullivan below:

Paul O’Sullivan and the Salesforce team will be sharing their invaluable insights at this year’s AI & Big Data Expo Global. O’Sullivan will feature on a day one panel titled ‘Converging Technologies – We Work Better Together’.

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From addressing the spectrum of use cases to navigating digital transformation, Shakir shed light on the challenges, ethical considerations, and the promising future of this groundbreaking technology.

Wide spectrum of use cases

Shakir highlighted the wide array of GenAI applications, ranging from productivity enhancements and research support to high-stakes areas such as strategic data mining and knowledge bots. She emphasised the transformational power of AI in understanding customer data, moving beyond simple sentiment analysis to providing actionable insights, thus elevating customer engagement strategies.

“GenAI now can take your customer insights to another level. It doesn’t just tell you whether something’s a positive or negative sentiment like old AI would do, it now says it’s positive or negative. It’s negative because X, Y, Z, and here’s the root cause for X, Y, Z,” explains Shakir.

Powering digital transformation

Gate One adopts an adaptive strategy approach, abandoning traditional five-year strategies for more agile, adaptable frameworks.

“We have a framework – our 5P model – where it’s: identify your people, identify the problem statement that you’re trying to solve for, appoint some partnerships, think about what’s the right capability mix that you have, think about the pathway through which you’re going to deliver, be use case or risk-led, and then proof of concept,” says Shakir.

By solving specific challenges and aligning strategies with business objectives, Gate One aims to drive meaningful digital transformation for its clients.

Assessing client readiness

Shakir discussed Gate One’s diagnostic tools, which blend technology maturity and operating model innovation questions to assess a client’s readiness to adopt GenAI successfully.

“We have a proprietary tool that we’ve built, a diagnostic tool where we look at blending tech maturity capability type questions with operating model innovation questions,” explains Shakir.

By categorising clients as “vanguard” or “safe” players, Gate One tailors their approach to meet individual readiness levels—ensuring a seamless integration of GenAI into the client’s operations.

Key challenges and ethical considerations

Shakir acknowledged the challenges associated with GenAI, especially concerning the quality of model outputs. She stressed the importance of addressing biases, amplifications, and ethical concerns, calling for a more meaningful and sustainable implementation of AI.

“Poor quality data or poorly trained models can create biases, racism, sexism… those are the things that worry me about the technology,” says Shakir.

Gate One is actively working on refining models and data inputs to mitigate such problems.

The future of GenAI

Looking ahead, Shakir predicted a demand for more ethical AI practices from consumers and increased pressure on developers to create representative and unbiased models.

Shakir also envisioned a shift in work dynamics where AI liberates humans from mundane tasks to allow them to focus on solving significant global challenges, particularly in the realm of sustainability.

Later this month, Gate One will be attending and sponsoring this year’s AI & Big Data Expo Global. During the event, Gate One aims to share its ethos of meaningful AI and emphasise ethical and sustainable approaches.

Gate One will also be sharing with attendees GenAI’s impact on marketing and experience design, offering valuable insights into the changing landscape of customer interactions and brand experiences.

As businesses navigate the evolving landscape of GenAI, Gate One stands at the forefront, advocating for responsible, ethical, and sustainable practices and ensuring a brighter, more impactful future for businesses and society.

Umbar Shakir and the Gate One team will be sharing their invaluable insights at this year’s AI & Big Data Expo Global. Find out more about Umbar Shakir’s day one keynote presentation here.

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Leveraging the power of NVIDIA’s AI foundry service on Microsoft Azure, Amdocs aims to meet the escalating demand for data processing and analysis in the telecoms sector.

The telecoms industry processes hundreds of petabytes of data daily. With the anticipation of global data transactions surpassing 180 zettabytes by 2025, telcos are turning to generative AI to enhance efficiency and productivity.

NVIDIA’s AI foundry service – comprising the NVIDIA AI Foundation Models, NeMo framework, and DGX Cloud AI supercomputing – provides an end-to-end solution for creating and optimising custom generative AI models.

Amdocs will utilise the AI foundry service to develop enterprise-grade LLMs tailored for the telco and media industries, facilitating the deployment of generative AI use cases across various business domains.

This collaboration builds on the existing Amdocs-Microsoft partnership, ensuring the adoption of applications in secure, trusted environments, both on-premises and in the cloud.

Enterprises are increasingly focusing on developing custom models to perform industry-specific tasks. Amdocs serves over 350 of the world’s leading telecom and media companies across 90 countries. This partnership with NVIDIA opens avenues for exploring generative AI use cases, with initial applications focusing on customer care and network operations.

In customer care, the collaboration aims to accelerate the resolution of inquiries by leveraging information from across company data. In network operations, the companies are exploring solutions to address configuration, coverage, or performance issues in real-time.

This move by Amdocs positions the company at the forefront of ushering in a new era for the telecoms industry by harnessing the capabilities of custom generative AI models.

(Photo by Danist Soh on Unsplash)

See also: Wolfram Research: Injecting reliability into generative AI

Want to learn more about AI and big data from industry leaders? Check out AI & Big Data Expo taking place in Amsterdam, California, and London. The comprehensive event is co-located with Digital Transformation Week.

Explore other upcoming enterprise technology events and webinars powered by TechForge here.

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The leak includes screenshots and videos showcasing a custom chatbot creator utilising GPT-4. This advanced version of ChatGPT boasts features such as web browsing and data analysis, enhancing its capabilities significantly.

According to the leaked information, OpenAI will introduce a new marketplace where users can share their custom chatbots or explore creations made by others.

The leaker, a Twitter user named CHOI, provided a summary of the anticipated updates:

Additionally, SEO tools developer Tibor Blaho shared a video demonstrating the user interface of the new feature—revealing a GPT Builder option that enables users to input prompts and create bespoke chatbots.

The GPT Builder interface offers a user-friendly experience, allowing individuals to select a default language, tone, and writing style for their chatbot. Users can configure the bot by providing a name, description, and instructions, along with the ability to upload files for a personalised knowledgebase.

The tool also allows toggling of features such as web browsing and image generation; giving users unprecedented control over their chatbot’s capabilities. Custom actions can be added to enhance the bot’s functionality.

Furthermore, the leaked information suggests that OpenAI plans to launch an enterprise-level “Team” subscription plan with both “Flexible” and “Annual” options.

The Team plan reportedly offers benefits such as unlimited high-speed GPT-4 usage and extended context capabilities, with a pricing structure of $25 per user, per month for the annual subscription and $30 per month for the non-annual option, requiring a minimum of three users.

OpenAI has recently rolled out several beta features for ChatGPT, including live web results, image generation, and voice chat.

The company is set to provide a preview of the new tools at the upcoming developer conference, offering the tech community a firsthand look at the future of conversational AI.

(Photo by Jem Sahagun on Unsplash)

See also: NIST announces AI consortium to shape US policies

Want to learn more about AI and big data from industry leaders? Check out AI & Big Data Expo taking place in Amsterdam, California, and London. The comprehensive event is co-located with Digital Transformation Week.

Explore other upcoming enterprise technology events and webinars powered by TechForge here.

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UK Prime Minister Rishi Sunak has spoken today on the global responsibility to confront the risks highlighted in the report and harness AI’s potential. Sunak emphasised the need for honest dialogue about the dual nature of AI: offering unprecedented opportunities, while also posing significant dangers.

“AI will bring new knowledge, new opportunities for economic growth, new advances in human capability, and the chance to solve problems we once thought beyond us. But it also brings new dangers and new fears,” said Sunak.

“So, the responsible thing for me to do is to address those fears head-on, giving you the peace of mind that we will keep you safe while making sure you and your children have all the opportunities for a better future that AI can bring.

“Doing the right thing, not the easy thing, means being honest with people about the risks from these technologies.”

The report delves into the rapid advancements of frontier AI, drawing on numerous sources. It highlights the diverse perspectives within scientific, expert, and global communities regarding the risks associated with the swift evolution of AI technology. 

The publication comprises three key sections:

1. Capabilities and risks from frontier AI: This section presents a discussion paper advocating further research into AI risk. It delineates the current state of frontier AI capabilities, potential future improvements, and associated risks, including societal harms, misuse, and loss of control.
2. Safety and security risks of generative AI to 2025: Drawing on intelligence assessments, this report outlines the potential global benefits of generative AI while highlighting the increased safety and security risks. It underscores the enhancement of threat actor capabilities and the effectiveness of attacks due to generative AI development.
3. Future risks of frontier AI: Prepared by the Government Office for Science, this report explores uncertainties in frontier AI development, future system risks, and potential scenarios for AI up to 2030.

The report – based on declassified information from intelligence agencies – focuses on generative AI, the technology underpinning popular chatbots and image generation software. It foresees a future where AI might be exploited by terrorists to plan biological or chemical attacks, raising serious concerns about global security.

Sjuul van der Leeuw, CEO of Deployteq, commented: “It is good to see the government take a serious approach, offering a report ahead of the Safety Summit next week however more must be done.

“An ongoing effort to address AI risks is needed and we hope that the summit brings much-needed clarity, allowing businesses and marketers to enjoy the benefits this emerging piece of technology offers, without the worry of backlash.”

The report highlights that generative AI could be utilised to gather knowledge on physical attacks by non-state violent actors, including creating chemical, biological, and radiological weapons.

Although companies are working to implement safeguards, the report emphasises the varying effectiveness of these measures. Obstacles to obtaining the necessary knowledge, raw materials, and equipment for such attacks are decreasing, with AI potentially accelerating this process.

Additionally, the report warns of the likelihood of AI-driven cyber-attacks becoming faster-paced, more effective, and on a larger scale by 2025. AI could aid hackers in mimicking official language, and overcome previous challenges faced in this area.

However, some experts have questioned the UK Government’s approach.

Rashik Parmar MBE, CEO of BCS, The Chartered Institute for IT, said: “Over 1,300 technologists and leaders signed our open letter calling AI a force for good rather than an existential threat to humanity.

“AI won’t grow up like The Terminator. If we take the proper steps, it will be a trusted co-pilot from our earliest school days to our retirement.

The AI Safety Summit will aim to foster healthy discussion around how to address frontier AI risks, encompassing misuse by non-state actors for cyberattacks or bioweapon design and concerns related to AI systems acting autonomously contrary to human intentions. Discussions at the summit will also extend to broader societal impacts, such as election disruption, bias, crime, and online safety.

Claire Trachet, CEO of Trachet, commented: “The fast-growing nature of AI has made it difficult for governments to balance creating effective regulation which safeguards the interest of businesses and consumers without stifling investment opportunities. Even though there are some forms of risk management and different reports coming out now, none of them are true coordinated approaches.

“The UK Government’s commitment to AI safety is commendable, but the criticism surrounding the summit serves as a reminder of the importance of a balanced, constructive, and forward-thinking approach to AI regulation.”

If the UK Government’s report is anything to go by, the need for collaboration around proportionate but rigorous measures to manage the risks posed by AI is more imperative than ever.

The global AI Safety Summit is set to take place at the historic Bletchley Park on 1 – 2 November 2023.

(Image Credit: GOV.UK)

See also: BSI: Closing ‘AI confidence gap’ key to unlocking benefits

Want to learn more about AI and big data from industry leaders? Check out AI & Big Data Expo taking place in Amsterdam, California, and London. The comprehensive event is co-located with Cyber Security & Cloud Expo and Digital Transformation Week.

Explore other upcoming enterprise technology events and webinars powered by TechForge here.

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