Tag: Generative Ai

Sebastian, can you start by sharing your background and what led you to your current role as VP of Engineering at Storyblok?

My journey in the tech industry began with a deep interest in software development and a passion for creating innovative solutions. Over the years, I have held various roles in engineering and management, which have provided me with a broad perspective on technology and its applications.

Before joining Storyblok, I worked with several startups and established companies, focusing on building scalable and secure software solutions. My experience in these diverse environments has been instrumental in shaping my approach to engineering and leadership. With Storyblok, I was drawn to the company’s vision of transforming content management and the opportunity to lead a talented team in driving this innovation forward.

In what ways can generative AI be utilized to create malicious content such as phishing emails and social engineering attacks?

Generative AI can produce highly realistic and personalized phishing emails by analyzing vast amounts of publicly available data about potential targets. This allows attackers to craft messages that are more likely to deceive recipients into divulging sensitive information. Similarly, AI can generate fake social media profiles or impersonate trusted contacts, enhancing the effectiveness of social engineering attacks. The ability to produce high-quality, contextually relevant content at scale means that these AI-generated threats can bypass many traditional security filters designed to catch generic phishing attempts.

The current cybersecurity measures seem adequate. What specific measures do you believe are most effective against AI-driven attacks?

While current cybersecurity measures provide a foundation, they need to be enhanced to effectively counter AI-driven attacks. Key measures include advanced threat detection where AI and machine learning are used to detect and respond to threats in real-time, behavioral analytics, which is the monitoring of user behavior to identify deviations that may indicate compromised accounts. Zero Trust Architecture is also important which involves implementing a model where verification is required for every access request, regardless of its origin.

Keeping staff informed about the latest threats and best practices to mitigate human error are also key measures in reducing the threat of AI-driven cyber attacks as is Multi-Factor Authentication (MFA) where an extra layer of security is added to verify user identities.

To Know More, Read Full Interview @ https://ai-techpark.com/aitech-interview-with-sebastian-gierlinger/

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Paige, kindly let our readers know how Seismic perceives the role of AI in evolving customer experiences and go-to-market (GTM) processes based on recent data.

At Seismic, we believe enablement is a mission-critical function that turns strategy into reality, and generative AI is creating an industry-defining moment for GTM and enablement teams. It is changing everything about the sales process, from prospecting to meeting preparation, content and presentation development, follow-up, training and performance tracking.

In fact, an overwhelming majority (93%) of enablement tech users acknowledge AI as the driving force behind their future investments. Based on this data, it’s evident that organizations neglecting to integrate AI into their GTM processes risk lagging behind and losing competitiveness in today’s industry, a sentiment echoed by 73% of respondents in our research.

What’s more: our customers know this to be true. In a Seismic customer survey, 65% of respondents cited AI as a primary reason for increased enablement investment. Specifically, they view Sales Content Generation & Optimization as the most valuable use cases to explore and implement for their teams. Over half (52%) are currently using or evaluating AI-powered tools within sales enablement processes, with 61% sharing that they are familiar with these tools to varying degrees.

Your report suggests a significant impact on both internal processes and customer experiences for businesses leveraging AI. How does Seismic observe this impact in terms of tangible ROI and enhanced customer engagement?

In addition to the clear revenue growth teams have witnessed, GTM leaders predict an average of 23% of that growth will be directly attributed to AI utilization over the next five years. In fact, 63% believe that AI is the primary force behind evolving customer experiences today. AI solutions are poised to touch nearly every corner of customer engagement.

For context, GTM leaders in the United States are leveraging AI-powered enablement tools for three primary functions: 53% utilize them for content analytics, 50% for content distribution, and 48% for learning and coaching. Businesses are experiencing significant benefits, with 91% of those who have implemented AI tools reporting an increase in customer satisfaction since integrating AI into their enablement processes.

How is Seismic addressing the gap in understanding how AI is used in GTM processes, and what educational initiatives or tools are being introduced without delving into specific numbers?

At Seismic, we work to consistently update our AI product offerings and tools to ensure they are meeting the needs of our customers and empowering them to build more strategic relationships, effectively engage with buyers, and speed up the entire buying process.

In fact, just last year we introduced an AI customer community, which is dedicated to sharing best practices, knowledge and strategies to seamlessly integrate AI into revenue teams’ operations. Additionally, we offer both the Seismic Advocacy Program and Seismic Community – two spaces for our customers to hear more directly from Seismic leadership about our products, as well as share with each other what they’re learning and doing with AI-powered enablement at their company.

To Know More, Read Full Interview @ https://ai-techpark.com/ai-transforming-gtm-processes/

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Generative AI has swiftly become popular among marketers and has the potential to grow to a $1.3 trillion industry in the next 10 years. OpenAI’s ChatGPT is just one growth example—rocketing to over 100 million users in just two months of its release.

Many have hailed generative AI as a process-changing tool that can quickly produce swaths of content with minimal human intervention, drastically scaling content production. That’s the claim anyway. But as AI becomes more prevalent, its use in content production opens several questions — does generative AI actually produce quality content? Can it match what human marketers can produce?

With the digital landscape already saturated with content, marketers in the AI era need to fully understand the strengths and weaknesses of current generative tools so they can build (and protect) high-quality connections with their audiences.

Human-generated content beat out AI-generated content in every category.

Though the AI tools had strengths in some areas, no one tool mastered multiple criteria across our tests. When it comes to accuracy, readability, and brand style and tone, the AI tools could not reach the level of quality that professional content writers provided. It also lacked the authenticity of human-written content.

The lesson: Brands and marketers must keep humans at the center of content creation.

Unsurprisingly, AI is not the end-all-be-all solution for creating content that truly connects with human audiences.  

Yes, AI is an efficient and capable tool that marketers can leverage to supercharge specific content tasks. Using AI for tasks such as research, keyword analysis, brainstorming, and headline generation may save content creators money, time, and effort.

Even so, marketers should prioritize humanity in their writing. AI can only give us an aggregate of the staid writing available across the internet. But highly skilled human writers are masters of contextualization, tapping into the subtleties of word choice and tone to customize writing to specific audiences.

As some have pointed out, quantity can never win out over quality.

In the race to adopt AI tools, we must remember what makes content valuable and why it connects with human audiences. The online marketing landscape is becoming increasingly competitive, and brands can’t risk the ability to build trusting connections with consumers in their rush to streamline workflows. Ultimately, humans must remain the central focus as brands invest in unique and authentic content that connects.

To Know More, Read Full Article @ https://ai-techpark.com/ai-vs-human-content-quality/

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The rapid advancement of AI has revolutionized industries worldwide, transforming the way businesses operate. While some organizations are still catching up, AI is undeniably a game-changer, reshaping industries and redefining enterprise operations.

Estimates from Goldman Sachs suggest that AI has the potential to increase global GDP by approximately 7% (almost $7 trillion) over the next decade by enhancing labor productivity. Even with conservative predictions, AI is poised to drive significant progress in the global economy.

The Importance of Training and Development

Training and development also play a critical role in this AI-driven evolution. Recent data showed that 66% of American IT professionals agreed it’s harder for them to take days off than their colleagues who are not in the IT department, which has serious implications for burnout, employee retention, and overall satisfaction. This makes AI integration more important than ever before. But first, proper training is essential.

As IT professionals are beginning to leverage AI’s power, emphasis must be placed on cultivating skills in data analysis, algorithm development, and system optimization. Especially as organizations embrace closed-loop AI systems, considerations around data security, ethics, and workforce upskilling become imperative.

AI companions are becoming increasingly essential to ensure efficient IT operations. Luckily, innovative solutions are emerging with capabilities like ticket summaries, response generation, and even AI solutions based on device diagnostics and ticket history to help streamline daily tasks and empower IT professionals to focus on higher-value issues.

Integrating Closed-Loop Systems to Supercharge Your AI Integration

The evolution of AI technology and closed-loop systems is set to revolutionize enterprise operations. As businesses navigate this future, embracing these advancements responsibly will be crucial for staying competitive and efficient. AI’s ability to enhance decision-making, streamline processes, and drive innovation opens new avenues for growth and success.

By integrating closed-loop systems and prioritizing responsible AI, enterprises can create more responsive and adaptive environments, ensuring continuous improvement and agility. The future of enterprise technology is here, and those who adapt and leverage these powerful tools responsibly will undoubtedly lead the way in their industries.

To Know More, Read Full Article @ https://ai-techpark.com/ai-evolution-enterprise-future/

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IT companies and consulting firms are on a relentless quest to stay innovative in a rapidly evolving digital world. Industries worldwide are embracing the digital landscape, using AI to help transform their operations and adapt to new challenges.

Digital transformation integrates digital technologies into all operational areas, streamlining processes, enhancing customer interactions, fostering a forward-thinking work culture, and improving overall strategic planning. By embracing digital transformation, companies have the potential to save money while maximizing efficiency.

A Grim Reality: Economic Challenges and Layoffs

In response to economic challenges, including significant layoffs in the tech sector, companies must innovate and adapt swiftly. Digital transformation, especially through AI, provides a lifeline.

In 2023, 1,186 tech companies laid off 262,682 employees and this year alone, 168 tech companies have laid off 42,324 employees. Major consulting firms are also at risk. This is forcing them to stay ahead of the curve and innovate before it is too late.

Why Digital Transformation Matters

Digital transformation, especially when incorporating AI, can be a strategic solution for the challenges in the tech sphere. Imagine this: a mid-sized IT company experiencing fast-declining revenues and an increase in operational costs integrates AI into its workflow. AI acts as a catalyst to streamline processes and reduce manual errors while freeing up time for employees to focus on more strategic tasks. This results in increased productivity, efficiency and profitability. This is what companies need to stay ahead of competition.

By 2027, AI tools are expected to be used for digital transformation to cut process costs in half and reduce modernization expenses by 70%.

But despite its potential, digital transformation is much more difficult for companies to adopt than it seems. Only 35% of businesses have successfully adopted digital transformation efforts which highlights a pressing issue: many organizations are not fully prepared to embrace digital change and integration.

Digital transformation is the future of business. By embracing it now, companies can turn challenges into growth opportunities and thrive in the evolving digital landscape. IT companies looking to protect and evolve their operations can rely on this approach to ultimately tackle economic challenges and layoffs. By investing in skill building, promoting innovation and planning accordingly, organizations can turn the challenges they face to opportunities of growth. While adopting digital transformation strategies may be difficult now, it is the future of business. Companies who embrace it can thrive in the evolving digital landscape.

To Know More, Read Full Article @ https://ai-techpark.com/ai-drives-digital-evolution/

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Hello Hussein, can you share with us your professional journey and how you became involved in the field of AI and technology, leading to your role as co-founder of Momentable?

I’ve always been fascinated with technology and sci-fi. AI is one of those things that sticks in your mind, and you can’t help but think about it.

I studied engineering and worked in tech, and even with all the advancements in technology we have been witnessing in the past two decades, AI was one of those things that we always thought would remain a sci-fi pipe dream for a long time.

This is not because there was nothing happening. But those who work in tech know it takes a while for the evolution of these technologies, and advancements are usually several degrees of separation from the regular user.

I’m always learning, reading, and building tech products, so AI was a field of study; however, implementing it was never accessible for early-stage products.

The status of AI has forever changed. OpenAI’s ChatGPT launch has had a remarkable impact on the field of AI and tech in general. AI is now available for regular users. People like me working in tech can now use AI in everything they are doing, which will accelerate product development and will impact the kind of products we can build and deliver to customers.

In addressing concerns surrounding AI ethics, you mentioned the importance of regulatory measures, technological transparency, and societal readiness. Could you elaborate on how Momentable approaches these areas to mitigate potential ethical dilemmas?

With great power comes great responsibility. AI is a powerful technology, and it’s very easy for those wielding it to amplify the impact of the good and the bad in the work they do.

While we, in the tech space, are doing our very best to build great products that deliver great value, we are not social scientists, psychologists, or public servants. So, we can’t be expected to regulate and supervise ourselves, nor can we evaluate the impact of these technologies and the products using them on the individual and on society.

It’s great when companies have values, codes of ethics, missions, and visions; however, those are not enough. Just like we do not rely on drivers to drive safely, we have traffic laws, signs, lights, and we make sure people driving a car are licensed and trained. We need to do the same with technologies, which, I would argue, have a massive impact on shaping our future as a species more than anything we’ve ever had in our history.

At Momentable, we are acutely aware of the impact of generative AI on our stakeholders, artists, cultural organizations, and art lovers. We engaged our stakeholders, ran several experiments where generative AI created artworks with input from artists, with their permission and consent.

In addition to using AI to enhance customer experience on our platform, we are using the learnings to evolve our product and introduce Generative AI in a thoughtful way that adds value and advances the art and culture space.

To Know More, Read Full Interview @ https://ai-techpark.com/aitech-interview-with-hussein-hallak/ 

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With data-driven decision-making now the best competitive advantage a company can have, business leaders will increasingly demand to get the information they need at a faster, more consumable clip. Because of this, we’ll continue to see calls for AI to become a business-consumer-friendly product rather than one that only technically savvy data scientists and engineers can wield. It’s this vision for the future that’s driving the five trends in AI-driven analysis that we see right now:

Users demand an explainable approach to data analysis

As AI technology advances, understanding the processes behind its results can be challenging. This “black box” nature can lead to distrust and hinder AI adoption among non-technical business users. However, explainable AI (XAI) aims to democratize the use of AI tools and make it more accessible to business users.

XAI generates explanations for its analysis and leverages conversational language, coupled with compelling visualizations, so non-data experts can easily interpret its meaning. XAI will be crucial in the future of AI-driven data analysis by bridging the gap between the complex nature of advanced models and the human need for clear, understandable, and trustworthy outcomes.

Multimodal AI emerges

Multimodal AI is the ultimate tool for effective storytelling in today’s data-driven world. While Generative AI focuses on creating new content, Multimodal AI can be seen as an advanced extension of Generative AI with its ability to understand and tie together information coming from different media simultaneously. For example, a multimodal generative model could process text to create a story and enhance it with pertinent images and sounds.

As data sets become more complex and robust, it’s become difficult to comprehensively analyze that data using traditional methods. Multimodal AI gives analytics teams the ability to consume and analyze heterogeneous input so they can uncover critical information that leads to better strategic decision-making.

Across all AI-driven analytics trends, it is crucial to emphasize AI safety and ethical practices as fundamental aspects in all areas of the business. For instance, Ethical AI is essential to help ensure that AI technologies are beneficial, fair, and safe to use. That is because AI models can inadvertently perpetuate biases present in the training data. As AI becomes increasingly personalized, incorporating a wider variety of data inputs and innovations, it is crucial that responsible AI governance and training are implemented across all levels of the organization. When everyone understands both the advantages and limits of AI, the future truly becomes brighter for all.

To Know More, Read Full Article @ https://ai-techpark.com/five-key-trends-in-ai-driven-analysis/ 

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Leslie, can you please introduce yourself and share your experience as a CEO and Founder at TurinTech?

As you say, I’m the CEO and co-founder at TurinTech AI. Before TurinTech came into being, I worked for a range of financial institutions, including Credit Suisse and Bank of America. I met the other co-founders of TurinTech while completing my Ph.D. in Computer Science at University College London. I have a special interest in graph theory, quantitative research, and efficient similarity search techniques.

While in our respective financial jobs, we became frustrated with the manual machine learning development and code optimization processes in place. There was a real gap in the market for something better. So, in 2018, we founded TurinTech to develop our very own AI code optimization platform.

When I became CEO, I had to carry out a lot of non-technical and non-research-based work alongside the scientific work I’m accustomed to. Much of the job comes down to managing people and expectations, meaning I have to take on a variety of different areas. For instance, as well as overseeing the research side of things, I also have to understand the different management roles, know the financials, and be across all of our clients and stakeholders.

One thing I have learned in particular as a CEO is to run the company as horizontally as possible. This means creating an environment where people feel comfortable coming to me with any concerns or recommendations they have. This is really valuable for helping to guide my decisions, as I can use all the intel I am receiving from the ground up.

To set the stage, could you provide a brief overview of what code optimization means in the context of AI and its significance in modern businesses?

Code optimization refers to the process of refining and improving the underlying source code to make AI and software systems run more efficiently and effectively. It’s a critical aspect of enhancing code performance for scalability, profitability, and sustainability.

The significance of code optimization in modern businesses cannot be overstated. As businesses increasingly rely on AI, and more recently, on compute-intensive Generative AI, for various applications — ranging from data analysis to customer service — the performance of these AI systems becomes paramount.

Code optimization directly contributes to this performance by speeding up execution time and minimizing compute costs, which are crucial for business competitiveness and innovation.

For example, recent TurinTech research found that code optimization can lead to substantial improvements in execution times for machine learning codebases — up to around 20% in some cases. This not only boosts the efficiency of AI operations but also brings considerable cost savings. In the research, optimized code in an Azure-based cloud environment resulted in about a 30% cost reduction per hour for the utilized virtual machine size.

To Know More, Read Full Interview @ https://ai-techpark.com/ai-tech-interview-with-leslie-kanthan/ 

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Bernard, kindly brief us about Generative AI and its impact on various industries such as retail, healthcare, finance, education, manufacturing, marketing, entertainment, sports, coding, and more?

Generative AI (GenAI) is revolutionizing multiple sectors by enabling the creation of new, original content and insights. In retail, it’s personalizing shopping experiences; in healthcare, it’s accelerating drug discovery and patient care customization. Finance is seeing more accurate predictive models, while education benefits from tailored learning materials. Manufacturing, marketing, entertainment, sports, and coding are all experiencing unprecedented innovation and efficiency improvements, showcasing GenAI’s versatility and transformative potential.

Your latest book, “Generative AI in Practice,” is set to release soon. Could you share some key insights from the book, including how readers can implement GenAI, its differences from traditional AI, and the generative AI tools highlighted in the appendix?

In “Generative AI in Practice,” I explore how GenAI differs fundamentally from traditional AI by its ability to generate novel content and solutions. The book offers practical guidance on implementing GenAI, highlighting various tools and platforms in the appendix that can kickstart innovation in any organization. It’s designed to demystify GenAI and make it accessible to a broader audience.

With your extensive experience advising organizations like Amazon, Google, Microsoft, and others, what role do you see GenAI playing in transforming business strategies and performance?

It’s clear that Generative AI (GenAI) is poised to become a pivotal element in reshaping business strategies and boosting performance across industries. By leveraging GenAI, companies can gain a significant competitive advantage through the acceleration of innovation, the automation of complex and creative tasks, and the generation of actionable insights. This transformative technology enables businesses to refine their decision-making processes and enhance customer engagement in ways previously unimaginable. As we move forward, the integration of GenAI into core business operations will not only optimize efficiency but also open up new avenues for growth and value creation, marking a new era in the corporate landscape.

Why is Generative AI considered the most powerful technology humans have ever had access to, and what makes it stand out compared to other advancements in the tech industry?

Generative AI not only stands out as perhaps the most potent technology available today due to its capacity for creativity and innovation, surpassing prior tech advancements by enabling machines to understand, innovate, and create alongside humans, but it also offers a pathway to artificial general intelligence (AGI). This potential to achieve AGI, where machines could perform any intellectual task that a human can, marks a significant leap forward. It represents not just an evolution in specific capabilities, but a foundational shift towards creating systems that can learn, adapt, and potentially think with the breadth and depth of human intelligence. This aspect of generative AI not only differentiates it from other technological advancements but also underscores its transformative potential for the future of humanity.

To Know More, Read Full Interview @ https://ai-techpark.com/aitech-interview-with-bernard-marr/ 

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Marketing organizations are increasingly adopting artificial intelligence to help analyze data, uncover insights, and deliver efficiency gains, all in the pursuit of optimizing their campaigns. The era of AI augmentation to assist marketing professionals will continue to gain momentum for at least the next decade. As AI becomes more pervasive, this shift will inevitably reshape the makeup and focus for marketing teams everywhere.

Humans will retain control of the marketing strategy and vision, but the operational role of machines will increase each year. By 2025, it is projected that 70% of lower-level administrative duties will largely disappear as artificial intelligence tools become more deeply entwined in the operations of marketing departments. Similarly, many analytical positions will become redundant, with smart chatbots expected to assume up to 60% of daily responsibilities.

However, the jobs forecast is not all doom and gloom because the demand for data scientists will explode. The ability to aggregate and analyze massive amounts of data will become one of the most sought-after skillsets for the rest of this decade. By 2028, the number of data science positions is expected to grow by 30%, remaining immune to economic pressures. These roles will be less susceptible to budget cuts, highlighting the critical importance of data analysis in the evolving marketing landscape.

Effects of the AI Rollout on Marketing Functions

As generative AI design tools are increasingly adopted, one thorny issue involves copyright protection. Many new AI solutions scrape visual content without being subjected to any legal or financial consequences. In the year ahead, a lot of energy and effort will be focused on finding a solution to the copyright problem by clarifying ownership and setting out boundaries for AI image creation. This development will drive precious cost and time savings by allowing marketing teams to embrace AI design tools more confidently, without the fear of falling into legal traps.

In addition, AI will become more pivotal as marketing teams struggle to scale efforts for customer personalization. The gathered intelligence from improved segmentation will enable marketing executives to generate more customized experiences. In addition, the technology will optimize targeted advertising and marketing strategies to achieve higher engagement and conversion levels.

By the end of 2024, most customer emails will be AI-generated. Brands will increasingly use generative AI engines to produce first drafts of copy for humans to review and approve. However, marketing teams will have to train large language models (LLMs) to fully automate customer content as a way of differentiating their brands. By 2026, this practice will be commonplace, enabling teams to shift their focus to campaign management and optimization.

To Know More, Read Full Article @ https://ai-techpark.com/future-of-marketing-with-ai-augmentation/ 

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