Month: August 2024

If Apple does eventually launch some kind of home robot, it may well have a next-gen AI assistant.

Apple is rumored to be tapping into the capabilities of generative AI to build a new ‘personality’ that could live inside upcoming robotic devices, potentially working in a similar way to how Siri currently operates on the iPhone.

That’s according to Mark Gurman at Bloomberg, who is one of the more reliable tipsters when it comes to future Apple products. Gurman has previously talked about Apple’s home robot plans, he’s now added more details about a potential AI assistant.

“While Siri is the digital assistant on Apple’s current devices, the company is working on another human-like interface based on generative AI,” Gurman writes. “It could run on the tabletop product and other future Apple robotics devices, I’m told.”

Apple wants that tabletop robot – perhaps something along the lines of the Amazon Astro – to cost less than $1,000 (about £760 / AU$1,475), according to Gurman. However, it sounds like these robotic devices are still very much at the early stages of development, and there are no guarantees that they’ll ever see the light of day.

Apple Intelligence everywhere

What we do know for sure is that Apple is making a lot of noise about Apple Intelligence, the suite of generative AI features – text creation, text summaries, image generation, and more – that are making their way to iPhones, iPads, and Mac computers later this year, together with other major software updates.

Given that Apple is now fully signed up to next-gen AI, it makes sense that it would be working on a project like a new robot personality – one that would be more capable and more natural in conversation than Siri is right now.

That said, we know that a lot of the generative AI smarts on Apple devices are going to be powered by ChatGPT, at least for the time being. Apple clearly has some catching up to do in this area before it can launch a generative AI chatbot of its own.

Gurman himself says there’s “a lot of promise” in Apple’s robotics work, while also admitting “it’s not clear” just how committed Apple will be to launching an actual home robot. Next up for the company is the launch of the iPhone 16.

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By putting the human at the center of AI development business leaders can build AI systems which truly enhance not just their organization but the wider society around them.

As we enter an era where technology could amplify the potential of human beings to unprecedented levels, ensuring trust and responsibility within AI has never been more important. AI innovation, and in particular generative AI, holds enormous opportunity to tackle challenges and problems for humans, but business leaders must tread carefully. 

To deal with problems such as bias, and ensure AI delivers real value, the approach to AI tools needs to be human-centric. Business leaders have an important role to play in how they implement this technology, both for their organizations and the wider world: AI should be in service of people, aligned with and embodying individual and organizational values, goals and aspirations.

For AI to be responsible it means that new systems need to be human-centered, inclusive, transparent and accountable. AI systems need to be subject to constant oversight and feedback from stakeholders, and must also be designed to work alongside, rather than replace, human expertise. AI truly holds the key to improve how all humans interact with technology, but a responsible approach is required, to get the most from it.

Building AI to solve problems

Generative AI creates value if it solves specific problems for specific people, and this should inform the way AI software is designed. By designing AI software for ‘personas’, such as those working in marketing, HR or finance, humans can be placed firmly at the center.

Business leaders should ensure they understand what each role or persona wants from AI, whether that be user-friendly, frictionless experiences, or greater agility and productivity. For instance, in the case of a developer, this could be code completion or for an agent, case summarization, which can translate more widely to everything from IT support to customer service to HR.

By taking this human-centric approach and focusing on the real challenges which employees and customers face every day, AI-driven solutions can deliver real value for the whole organization. Continuous feedback from employees and customers helps to shape AI solutions providing consistent and lasting value, and most importantly, a technology which is fair and open for all to use.

Breaking down barriers

Inclusivity and accessibility are central to improving the way human beings interact with technology. The ability of multilingual and multimodal AI models to understand anything in multiple languages will be an important way to break down barriers for the people who work with AI. Tomorrow’s AI models will be able to understand multiple inputs such as video and images, meaning easier access to technology, regardless of language and location, and enabling teams to work together across the world.

AI translation software can also ensure that international teams can enjoy seamless communication across the enterprise. For agents, this means that customer and employee issues can be resolved faster in real-time, regardless of the original language the issue was raised in. For everyone though, this means help and understanding can be given in a more equitable way than previously.

Levelling the playing field

Generative AI interfaces, alongside low-code and no-code applications can enable business users to be ‘hands-on’ with developing applications. This not only accelerates digital transformation efforts by empowering business users to build basic digital workflows, but can also boost productivity and job satisfaction, with text-to-code helping anyone create new applications with simple text inputs.

Generative AI frees up highly trained developers to focus on more mission-centric applications. For said developers, AI ‘companions’ will simplify coding and the construction of flows: this rapid automation in turn can help organizations reduce IT backlogs and drive innovations. For smaller organizations, text-to-code and low-code can be game-changing.

Diversity and bias

Bias in AI is a real and ongoing problem, affecting everything from credit scoring to job applications to the images generated by AI systems. Business leaders have to consider the technology’s real-world impact on the people who use it and interface with it, and also think carefully about any AI system’s impact on society as a whole. This societal and environmental impact should be considered at every stage of AI product development.

Both the teams which train, test and use such systems, and the datasets used in training should reflect the diversity of society, to ensure that the tools avoid pitfalls such as bias. Business leaders must work to ensure that AI technology serves as wide a range of needs as possible.

It’s important at an early stage to acknowledge and be transparent around the trade-offs that come with using AI. This in turn can spark meaningful conversations with customers about managing challenges, rather than simply wishing them away. To take just one example, it’s impossible to get rid of AI bias entirely, but by taking a careful approach to AI training and to the teams hired to deal with AI, business leaders can recognize and mitigate the problem.

A brighter future

By putting the human at the center of AI development and taking a transparent, inclusive and accountable approach, business leaders can build AI systems which truly enhance not just their organization but the wider society around them.

Business leaders must ensure that teams and datasets are diverse, and keep the ‘human in the loop’ with constant feedback from all stakeholders. This collaborative approach will be key to developing safe and accessible AI, with continuous improvement driven by insights and feedback from real-world performance. By centering AI on human needs, human goals and human values, business leaders can be sure they can create a brighter future.

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This article was produced as part of TechRadarPro’s Expert Insights channel where we feature the best and brightest minds in the technology industry today. The views expressed here are those of the author and are not necessarily those of TechRadarPro or Future plc. If you are interested in contributing find out more here: https://www.techradar.com/news/submit-your-story-to-techradar-pro

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How GenAI is impacting digital transformation for businesses, dispelling myths surrounding AI and no-code.

To say AI has great potential feels like the biggest understatement of the year. Since the launch of ChatGPT in particular, terms that were reserved for technical specialists such as generative AI and LLMs have become mainstream.

However, that explosion of conversation and a scramble to incorporate AI tools into business workflows or find a valid way to describe an organization’s solution as ‘AI-powered’ in marketing copy has led many to the question of the moment. Are the applications of AI, and in particular generative AI, being over-hyped?

Journalists, analysts, and buyers alike are becoming fatigued by the constant nod to the emerging technology and are asking questions about whether AI can actually solve complex business challenges outside of the sandbox, today.

The rise and limitations of SaaS

To answer this, it’s useful to look at the recent evolution of digital transformation in businesses. The development of cloud computing has led to increased integration of software to drive transformation, leading to a surge of applications and services and the rise of SaaS.

Predictions say that cloud-native applications will soon match the numbers of apps developed over the last four decades. Businesses are choosing to go cloud-native because of the ability it provides to cater to specific digital transformation needs, while SaaS has in turn replaced legacy solutions because it can handle the increased demand for cloud-native apps.

However, the issue with SaaS is that the one-size-fits-all nature of these solutions are not always the best fit for individual sectors and business needs, undermining that very objective of using digital transformation to address needs that are specific to a business in order to gain and maintain and a competitive edge. What’s more, multiple competitors using the same ‘out-of-the-box’ SaaS solutions soon begin to appear homogenous to customers.

Finding a way to mine the core simplification and speed benefits of SaaS while customizing applications to individual business needs has become the core challenge of digital transformation today.

No-code and GenAI: a perfect pairing

This is where no-code technology has entered the conversation. No-code platforms allow users who don’t have formal training in software development to develop applications using visual drag-and-drop tools. Far from needing to understand a programming language, the only skills that are really necessary when using no-code platforms to develop business applications are problem-solving and, crucially, a good understanding of the business and its processes. Combining these two things ensures applications are optimized to the organization’s individual needs.

No-code fuses the speed and accessibility of SaaS and the customization qualities of traditional software development by offering businesses a way to democratize the process of developing applications. It helps enterprises meet their application backlogs by helping to address use cases from customer-facing applications to workflows, where every employee can quickly and easily contribute to solving unique business challenges.

GenAI also comes into play here as a powerful catalyst for no-code development; this is a great example of where AI can already be making a huge difference in any enterprise today in a very simple way. It allows enterprises to streamline application development and hugely speed up the process by automating tasks. For example, it can be used to convert user requests straight into application templates or frameworks, eliminating a whole step from the development process.

It can be used to automate and speed up workflows and processes across a business, from project management to customer privacy and regulatory compliance, to employee lifecycle management. One government institution used this technology to roll out an application to thousands of users to automate complicated project management processes – 95% of the app was built without the institution needing to write a single line of code.

Myth-busting GenAI and no-code

GenAI and no-code technologies are being used together as part of a natural progression of digital transformation. Far from replacing jobs, they are fueling the speed of innovation by creating citizen developers out of employees, helping them build applications which work specifically towards the distinct goals of the business, automating mundane tasks, and freeing up developers and other departments to focus on those activities that are really going to move the needle.

The no-code market is forecast to generate $187 billion in revenue by 2030, growing from $10.3 billion in 2019, matching the growing demand for more and more specific software applications and showing the appetite for a tool that offers freedom and flexibility to design applications that not only work for their business but become the driving force behind its competitive edge.

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This article was produced as part of TechRadarPro’s Expert Insights channel where we feature the best and brightest minds in the technology industry today. The views expressed here are those of the author and are not necessarily those of TechRadarPro or Future plc. If you are interested in contributing find out more here: https://www.techradar.com/news/submit-your-story-to-techradar-pro

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