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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The release comes on the heels of an expanded partnership with Google that provides Anthropic access to advanced processing hardware, enabling the substantial expansion of Claude’s context-handling capabilities.

With the ability to process lengthy documents like full codebases or novels, Claude 2.1 is positioned to unlock new potential across applications from contract analysis to literary study. 

The 200K token window represents more than just an incremental improvement—early tests indicate Claude 2.1 can accurately grasp information from prompts over 50 percent longer than GPT-4 before the performance begins to degrade.

Anthropic also touted a 50 percent reduction in hallucination rates for Claude 2.1 over version 2.0. Increased accuracy could put the model in closer competition with GPT-4 in responding precisely to complex factual queries.

Additional new features include an API tool for advanced workflow integration and “system prompts” that allow users to define Claude’s tone, goals, and rules at the outset for more personalised, contextually relevant interactions. For instance, a financial analyst could direct Claude to adopt industry terminology when summarising reports.

However, the full 200K token capacity remains exclusive to paying Claude Pro subscribers for now. Free users will continue to be limited to Claude 2.0’s 100K tokens.

As the AI landscape shifts, Claude 2.1’s enhanced precision and adaptability promise to be a game changer—presenting new options for businesses exploring how to strategically leverage AI capabilities.

With its substantial context expansion and rigorous accuracy improvements, Anthropic’s latest offering signals its determination to compete head-to-head with leading models like GPT-4.

(Image Credit: Anthropic)

See also: Paul O’Sullivan, Salesforce: Transforming work in the GenAI era

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.

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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.

The post Amdocs, NVIDIA and Microsoft Azure build custom LLMs for telcos appeared first on AI News.

Their new research report, The Generative AI Tipping Point, sheds light on the challenges faced by organisations as generative AI technology becomes more prevalent in the workplace.

The report delves into how organisations are dealing with the use of generative AI tools, revealing a significant cognitive dissonance among IT and security leaders. Astonishingly, 73 percent of these leaders confessed that their employees frequently use generative AI tools or Large Language Models (LLM) at work. Despite this, a staggering majority admitted to being uncertain about how to effectively address the associated security risks.

When questioned about their concerns, IT and security leaders expressed more worry about the possibility of inaccurate or nonsensical responses (40%) than critical security issues such as exposure of customer and employee personal identifiable information (PII) (36%) or financial loss (25%).

Raja Mukerji, Co-Founder and Chief Scientist at ExtraHop, said: “By blending innovation with strong safeguards, generative AI will continue to be a force that will uplevel entire industries in the years to come.”

One of the startling revelations from the study was the ineffectiveness of generative AI bans. About 32 percent of respondents stated that their organisations had prohibited the use of these tools. However, only five percent reported that employees never used these tools—indicating that bans alone are not enough to curb their usage.

The study also highlighted a clear desire for guidance, particularly from government bodies. A significant 90 percent of respondents expressed the need for government involvement, with 60 percent advocating for mandatory regulations and 30 percent supporting government standards for businesses to adopt voluntarily.

Despite a sense of confidence in their current security infrastructure, the study revealed gaps in basic security practices.

While 82 percent felt confident in their security stack’s ability to protect against generative AI threats, less than half had invested in technology to monitor generative AI use. Alarmingly, only 46 percent had established policies governing acceptable use and merely 42 percent provided training to users on the safe use of these tools.

The findings come in the wake of the rapid adoption of technologies like ChatGPT, which have become an integral part of modern businesses. Business leaders are urged to understand their employees’ generative AI usage to identify potential security vulnerabilities.

You can find a full copy of the report here.

(Photo by Hennie Stander on Unsplash)

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 Digital Transformation Week.

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DALL-E 3 promises significant enhancements over its predecessors and introduces seamless integration with ChatGPT.

One of the standout features of DALL-E 3 is its ability to better understand and interpret user intentions when confronted with detailed and lengthy prompts:

"A middle-aged woman of Asian descent, her dark hair streaked with silver, appears fractured and splintered, intricately embedded within a sea of broken porcelain. The porcelain glistens with splatter paint patterns in a harmonious blend of glossy and matte blues, greens,… pic.twitter.com/QryQz0BtxB

— OpenAI (@OpenAI) September 20, 2023

Even if a user struggles to articulate their vision precisely, ChatGPT can step in to assist in crafting comprehensive prompts.

DALL-E 3 has been engineered to excel in creating elements that its predecessors and other AI generators have historically struggled with, such as rendering intricate depictions of hands and incorporating text into images:

"An illustration of a human heart made of translucent glass, standing on a pedestal amidst a stormy sea. Rays of sunlight pierce the clouds, illuminating the heart, revealing a tiny universe within. The quote 'Find the universe within you' is etched in bold letters across the… pic.twitter.com/S3cKMkG67T

— OpenAI (@OpenAI) September 20, 2023

OpenAI has also implemented robust security measures, ensuring the AI system refrains from generating explicit or offensive content by identifying and ignoring certain keywords in prompts.

Beyond technical advancements, OpenAI has taken steps to mitigate potential legal issues. 

While the current DALL-E version can mimic the styles of living artists, the forthcoming DALL-E 3 has been designed to decline requests to replicate their copyrighted works. Artists will also have the option to submit their original creations through a dedicated form on the OpenAI website, allowing them to request removal if necessary.

OpenAI’s rollout plan for DALL-E 3 involves an initial release to ChatGPT ‘Plus’ and ‘Enterprise’ customers next month. The enhanced image generator will then become available to OpenAI’s research labs and API customers in the upcoming fall season.

As OpenAI continues to push the boundaries of AI technology, DALL-E 3 represents a major step forward in text-to-image generation.

(Image Credit: OpenAI)

See also: Stability AI unveils ‘Stable Audio’ model for controllable audio generation

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.

The post OpenAI reveals DALL-E 3 text-to-image model appeared first on AI News.