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Claire chatted to Didem Gurdur Broo from Uppsala University about how to shape the future of robotics, autonomous vehicles, and industrial automation.

Didem Gurdur Broo is an Assistant Professor and Associate Senior Lecturer at the Department of Information Technology at Uppsala University. She leads the Cyber-physical Systems Lab, directing research on intelligent systems like collaborative robots, autonomous vehicles, and smart cities. Didem is a computer scientist with a PhD in mechatronics, which can give you an idea about how much she loves to talk about the future and emerging technologies. She dreams a better world and actively works on improving inequalities regardless of their nature.

We humans excel at generalization. If you taught a toddler to identify the color red by showing her a red ball, a red truck and a red rose, she will most likely correctly identify the color of a tomato, even if it is the first time she sees one.

While we move through 2025, pen and paper remain as familiar on construction sites as ever, and many construction managers still rely on intuition and experience over the promises of technology or robotic innovation.

Recent advances in robotics and artificial intelligence (AI) are enabling the development of a wide range of systems with unique characteristics designed for varying real-world applications. These include robots that can engage in activities traditionally only completed by humans, such as sketching, painting and even hand-writing documents.

As part of the ongoing war in Ukraine, one night in late November, Russia sent a swarm of 188 drones to attack Ukrainian infrastructure like electrical utilities, as well as residential areas, according to news reports. Ukrainian forces said they shot down 76 drones, but the damage was still extensive. Those kinds of attacks are continuing almost daily now.

Generative AI holds incredible promise, but its potential is often blocked by poor app experiences. 

AI leaders aren’t just grappling with model performance — they’re contending with the practical realities of turning generative AI into user-friendly applications that deliver measurable enterprise value.

Infrastructure demands, unclear output expectations, and complex prototyping processes stall progress and frustrate teams.

The rapid pace of AI innovation has also introduced a growing patchwork of tools and processes, forcing teams to spend time on integration and basic functionality instead of delivering meaningful business solutions.

This blog explores why AI teams encounter these hurdles and offers actionable solutions to overcome them.

What stands in the way of effective generative AI apps?

While teams move quickly on technical advancements, they often face significant barriers to delivering usable, effective business applications: 

• Technology complexity: Building the infrastructure to support generative AI apps — from vector databases to Large Language Model (LLM) orchestration — requires deep technical expertise that most organizations lack. Choosing the right LLM for specific business needs adds another layer of complexity.

• Unclear objectives: Generative AI’s unpredictability makes it hard to define clear, business-aligned objectives. Teams often struggle to connect AI capabilities into solutions that meet real-world needs and expectations.

• Talent and expertise: Generative AI moves fast, but skilled talent to develop, manage, and govern these applications is in short supply. Many organizations rely on a patchwork of roles to fill gaps, increasing risk and slowing progress.

• Collaboration gaps: Misalignment between technical teams and business stakeholders often results in generative AI apps that miss expectations — both in what they deliver and how users consume them.

• Prototyping barriers: Prototyping generative AI apps is slow and resource-intensive. Teams struggle to test user interactions, refine interfaces, and validate outputs efficiently, delaying progress and limiting innovation.

• Hosting difficulties: High computational demands, integration complexities, and unpredictable outcomes often make deployment challenging. Success requires not only cross-functional collaboration but also robust orchestration and tools that can adapt to evolving needs. Without workflows that unite processes, teams are left managing disconnected systems, further delaying innovation.

The result? A fractured, inefficient development process that undermines generative AI’s transformative potential.

Despite these app experience hurdles, some organizations have navigated this landscape successfully. 

For example, after carefully evaluating its needs and capabilities, The New Zealand Post — a 180-year-old institution — integrated generative AI into its operations, reducing customer calls by 33%.

Their success highlights the importance of aligning generative AI initiatives with business goals and equipping teams with flexible tools to adapt quickly.

Turn generative AI challenges into opportunities

Generative AI success depends on more than just technology — it requires strategic alignment and robust execution. Even with the best intentions, organizations can easily misstep.

Overlook ethical considerations, mismanage model outputs, or rely on flawed data, and small mistakes quickly snowball into costly setbacks.

AI leaders must also contend with rapidly evolving technologies, skill gaps, and mounting demands from stakeholders, all while ensuring their models are secure, compliant, and reliably perform in real-world scenarios.

Here are six strategies to keep your initiatives on track:

1. Business alignment and needs assessment: Anchor your AI initiatives to your organization’s mission, vision, and strategic objectives to ensure meaningful impact.
   
   
2. AI technology readiness: Assess your infrastructure and tools. Does your organization have the tech, hardware, networking, and storage to support generative AI implementation? Do you have tools that enable seamless orchestration and collaboration, allowing teams to deploy and refine models quickly?
   
   
3. AI security and governance: Embed ethics, security, and compliance into your AI initiatives. Establish processes for ongoing monitoring, maintenance, and optimization to mitigate risks and ensure accountability.
   
   
4. Change management and training: Foster a culture of innovation by building skills, delivering targeted training, and assessing readiness across your organization.
   
   
5. Scaling and continuous improvement: Identify new use cases, measure and communicate AI impact, and continually refine your AI strategy to maximize ROI. Focus on reducing time-to-value by adopting workflows that are adaptable to your specific business needs, ensuring that AI delivers real, measurable outcomes.
   

Generative AI isn’t an industry secret — it’s transforming businesses across sectors, driving innovation, efficiency, and creativity.

Yet, according to our Unmet AI Needs survey, 66% of respondents cited difficulties in implementing and hosting generative AI applications. But with the right strategy, businesses in virtually every industry can gain a competitive edge and tap into AI’s full potential. 

Lead the way to generative AI success

AI leaders hold the key to overcoming the challenges of implementing and hosting generative AI applications. By setting clear goals, streamlining workflows, fostering collaboration, and investing in scalable solutions, they can pave the way for success.

To achieve this, it’s critical to move beyond the chaos of disconnected tools and processes. AI leaders who unify their models, teams, and workflows gain a strategic advantage, enabling them to adapt quickly to changing demands while ensuring security and compliance.

Equipping teams with the right tools, targeted training, and a culture of experimentation transforms generative AI from a daunting initiative into a powerful competitive advantage.

Want to dive deeper into the gaps teams face with developing, delivering, and governing AI? Explore  our Unmet AI Needs report for actionable insights and strategies.

The post Solving the generative AI app experience challenge appeared first on DataRobot.

The culmination of the challenge will be in-person presentations to industry, investors, and community members at the Robotics Summit & Expo in Boston from April 30 to May 1st.

Experts highlight the need for a clear framework when it comes to AI research, given the rapid adoption of artificial intelligence by children and adolescents using digital devices to access the internet and social media.

Research in the International Journal of Computational Vision and Robotics could lead to faster and more accurate robots for high-precision tasks in factories.

DEEP Robotics develops a range of advanced robotic platforms, each designed for specific real-world applications across industrial, public service, and research sectors.

Lite3 is an agile quadruped platform ideal for education, research, and light industrial tasks, offering versatility for developing AI and robotics solutions.
Lite3 supports open source, users can develop advanced perception capabilities such as autonomous navigation, automatic obstacle avoidance, visual localization, environment reconstruction, customizable API for robotics development and AI training

Image credit: Deep Robotics – deeprobotics.cn

X30, a robust quadruped, is tailored for inspection, security, and autonomous navigation in hazardous environments such as industrial sites and power plants.
X30 robot dog conducts autonomous inspection day and night in any weather stably, the operating temperature range of X30 has been extended to between minus 20°C and plus 55°C, the load capacity can be up to 85KG

Image credit: Deep Robotics – deeprobotics.cn

DEEP Robotics Lynx, an off-road wheeled quadruped, is built for outdoor exploration, search-and-rescue missions, providing unmatched mobility on uneven terrain.
DEEP Robotics Lynx all-terrain robot features an agile design and powerful multi-terrain adaptability, combined with a distinctive wheel-legged movement system and AI driven, striking an ideal balance between speed and agility

Image credit: Deep Robotics – deeprobotics.cn

DR01 humanoid robot showcases advanced locomotion for dynamic human-like motion, contributing to research in human-robot interaction and service robotics for task automation.
DR01 humanoid robot boasts highly flexible movement capabilities, adapts to complex environments, and integrates sensing/perception abilities and powerful autonomous learning capabilities

Image credit: Deep Robotics – deeprobotics.cn

Various Challenges for the systems above: Enhancing autonomy, improving power efficiency, and refining adaptability to diverse environments.

Future Goals for the systems:
Integrating AI-driven perception systems for smarter navigation.
Expanding industrial, public safety, and service applications.
Developing robots for seamless, collaborative human-robot interactions with superior performance in real-world scenarios.

Videos:
https://www.youtube.com/watch?v=zxGwOEYYFVo
https://www.youtube.com/watch?v=NNkxlKLMoMM&t=19s
https://www.youtube.com/watch?v=iL833P0Vino
https://www.youtube.com/watch?v=lCFyfh3mLOQ

The content and media above is provided to us by Deep Robotics. www.deeprobotics.cn

Scientists have developed a computing chip that can learn, correct errors, and process AI tasks.

Celebrating its 10th anniversary, global robot programming software company RoboDK reflects on a decade improving robot deployment. In this Q&A CEO Albert Nubiola looks ahead to continue their mission of making robotics accessible to all.

A team of roboticists at Sony Computer Science Laboratories Inc. and the NeuroPiano Institute, in Kyoto, reports that a robotic exoskeleton strapped to the top of a piano player's hand allowed it to control the player's fingers during speed exercises, leading to improvements in playing fast-moving piano tunes. In their study, published in the journal Science Robotics, the group conducted experiments with their exoskeleton hand robot with more than 100 trained piano players.

Copilot in Microsoft 365: AI-Powered Assistance

Microsoft has been a pioneer in implementing artificial intelligence (AI) into business tools. And its latest breakthrough, Copilot (integrated into the Microsoft 365 suite), is a game changer.

This is much more wondrous for the organizations since AI in Microsoft 365 can automate most routine chores and make them have greater efficiency as well as better coordination among varied teams, departments, and projects. It gives effective communication, enhances the management of projects in a more optimal manner, and provides even deeper insights from data without requiring sophisticated technical expertise.

In this article, we are going to address the changes that Copilot has introduced in terms of productivity and how it brings AI advantage into competition by businesses. Main Benefits, Practical mobile Applications, and Future Possibility of Copilot Along with the challenges that the enterprise may face, we also discuss.

Key features of Copilot in Microsoft 365

1. AI-Enhanced Document Creation and Editing

One of Copilot’s most significant capabilities is its ability to let you create and edit documents in Word and PowerPoint. Copilot helps professionals make the work of drafting reports, proposals, or presentations less burdensome. It gives users real-time suggestions, corrects language, and even helps format them. Copilot ensures that information is clear, concise, and professional by reading into the context in which information is created. In PowerPoint, it goes a step further to recommend design elements and help you build visually beautiful presentations without requiring design skills.

2. Automated Excel Data Analysis

Data analysis is a crucial and stressful process in many business situations. However, it can be greatly simplified by Copilot’s Excel features. It supports users by automating data analysis, creating charts, and offering insights without the need for advanced Excel skills. Copilot can also suggest formulas, automate repetitive activities, and assist users in identifying data patterns. This makes it an effective tool for corporate teams seeking precise and timely data to make informed decisions. As a result, data processing speed improves, errors are reduced, and insights can be applied faster.

3. AI-Powered Email Assistance in Outlook

This is achieved through the copilot that is in Microsoft Outlook email management. It uses AI since it will help in drafting, responding and can even send out structured e-mails. It allows one to be able to see to it that style is uniform while writing communications. Also, it can automate follow ups and reminders of unread messages and draft messages thereby keeping teams on top of their communication without putting too much work.

4. Meeting and Task Management in Teams

The feature of Copilot under Microsoft Teams for cooperation management offers you planning of meetings, generation of meeting notes, and assigning responsibilities to members. Based on deadlines and relevance, Copilot can offer prioritization of work by teams; therefore, teams tend to be on track and well-organized. Its ability to track progress and communicate real-time updates to the team also upsurges efficiency and keeps everyone in sync.

Microsoft 365 Copilot’s Practical Uses for a Range of Business Purposes

1. Sales and Marketing

Copilot helps to enhance the performance of the marketing and sales divisions. It helps the sales team to speed up the documentation and proposal preparation process by gaining insights from previous proposals. This reduces administrative work and allows them to focus on strategy and relationship-building. Copilot may also assist with campaign creation in marketing by producing email templates, social media posts, and marketing reports. It allows marketers to analyze consumer behavior more quickly and plan improvements accordingly.

2. Recruitment and Human Resources

Copilot’s capabilities aid human resource teams, especially in running multiple workflows. For example, Copilot could assist the human resources manager in organizing employee performance reports, performing application follow-ups, and making employee offer letters. These factors not only decrease the administrative burden but also enhance the consistency of communications throughout the organization. The way Copilot can scan through resumes and match individuals to the requirements of a job while automatically scheduling interviews for recruitment teams, HR professionals can focus on building stronger teams.

3. Accounting and Finance

Finance departments can use Copilot’s Excel functionality to enhance their reporting and analysis processes. Copilot reduces the time needed for manual audits as it helps to create financial reports, forecast budgets, and even detect inconsistencies. It reduces human error by automating routine accounting operations that include cost tracking, reconciliation, and invoicing. Finance teams can make smarter, faster financial choices using Copilot’s real-time insights about profitability, cash flow, and other key financial indicators.

4. Client Assistance and Support

Using Copilot, the customer support team can automate ticket prioritizing, respond to FAQs with AI, and even follow up with clients when needed. This ensures that clients receive only accurate and consistent information. Additionally, it also speeds up the response times. For example, Copilot can provide responses based on previous encounters. So, the support team can handle customer requests quickly and concentrate on complicated problems.

Security, Compliance, and Privacy of Copilot

Businesses have to consider privacy and security when using AI-powered solutions like Copilot. Microsoft has taken these considerations to make sure Copilot is a safe and dependable solution.

1. Privacy and Data Security

Microsoft developed Copilot as part of Microsoft 365’s multi-layered security and robust encryption mechanisms. Copilot’s encryption technology protects sensitive data during transmission and storage.  Furthermore, Microsoft complies with foreign privacy regulations, such as GDPR, ensuring that organizations’ data is managed properly and according to international laws. So, enterprises may apply AI without fear of security risks.

2. Compliance

For industries like law, finance, and healthcare, compliance is essential. Copilot maintains compliance by looking for any possible legal problems in emails, papers, and other company communication. It alerts users when any information deviates from compliance guidelines to prevent expensive legal troubles. For instance, it can guarantee that financial reports adhere to relevant industry standards or that HIPAA requirements are followed when handling sensitive healthcare data.

The Future of AI in Microsoft 365 and Business Workflows

The future of artificial intelligence in Microsoft 365 is full of possibilities for changing how businesses work. Copilot is already a big step toward bringing AI into everyday tasks, but it’s just the start. As artificial intelligence technology advances, Microsoft will continue to introduce new features that make it smarter and easier to use. Businesses should expect changes that will allow them to get more done with less effort.

One of the best features of artificial intelligence is its ability to learn and develop over time. Copilot learns from its users and adapts to their demands. As a result, the more time you spend using it, the more valuable it becomes. As AI evolves and improves, it provides relevant solutions that enable organizations to make better decisions.

Conclusion

Copilot in Microsoft 365 is more than just an automation tool. It’s a sophisticated AI assistant that helps businesses operate smarter and quicker. Copilot can be integrated into Microsoft Office programs like Word, Excel, Outlook, and Teams to handle repetitive work. This allows the employees to focus on what truly matters—strategic decision-making and creativity.

Copilot helps businesses stay productive in a fast-paced environment by improving document generation, streamlining data analysis, improving communication, and assisting with task management. It guarantees that assignments are finished on time, through improved individual and team communication.

USM Business Systems specializes in developing custom AI solutions that increase productivity. We can assist you in implementing Copilot and other AI solutions into your company to increase productivity and stay ahead of the competition. To learn more about how artificial intelligence could benefit your business, get in contact with us right now.

 

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Writer Gary Grossman concludes the new Trump presidency could spell good times ahead for AI writing and related AI apps.

Observes Grossman: “Without a single debate question or major campaign promise about AI, voters inadvertently tipped the scales in favor of accelerationists — those who advocate for rapid AI development with minimal regulatory hurdles.”

Adds Grossman: Trump’s “party platform has little to say about AI.

“However, it does emphasize a policy approach focused on repealing AI regulations.”

In other news and analysis on AI writing:

*Give ChatGPT a Standardized Personality – Including One that Edits: ChatGPT has come out with a new feature that enables you to create a standardized personality for the AI.

Essentially, you can now program ChatGPT to assume the personality and skills of a witty copy editor with deep knowledge of AI and a penchant for detail, for example — and rest assured that ChatGPT will assume that personality each time you log-on.

Before the new feature, users already had the ability to create the same personality for ChatGPT – but the prompt for the personality needed to be loaded into ChatGPT’s message box before each use.

*Google Using a Competitor to Improve Its AI Writer/Chatbot: In an ironic twist, Google is using competitor Anthropic Claude to help improve its own AI chatbot.

Dubbed Google Gemini, the tech titan’s answer to ChatGPT is often used by communicators for AI writing, research and related tasks.

Writer Charles Rollet says Google contractors are using chat responses offered by Anthropic Claude as a benchmark for Gemini to match – or beat.

*ChatGPT Rolls-Out Its Version of ‘Agents Lite:’ ChatGPT has a new feature that enables users to create basic, AI agents.

Dubbed ‘Scheduled Tasks,’ writers will be able to use the AI to create simple agents, for example, that can perform one or more research tasks for them on a daily basis – or simply deliver customized news on a daily basis.

Scheduled Tasks are already supported in ChatGPT Web, iOS, Android and MacOS.

And they’re promised to appear in the Windows desktop app later in Q1.

Meanwhile, OpenAI is also working on a still-in-development module promising the ability to create much more powerful agents, dubbed ‘Operator.’

*Microsoft Unveils ‘Pay-As-You-Go’ Agents: In a move destined to appeal to the frugal, Microsoft now allows Copilot 365 users to develop autonomous agents on a pay-as-you-go basis.

Observes writer Sabrina Ortiz: “The costs are determined by the sum of messages used by your organization, with message usage varying depending on the agent’s complexity — and use of specific features, according to Microsoft.

“IT admins stay in control, with the ability to create organization-wide agents and manage agent deployment.”

*More Desktop Apps Now Work With ChatGPT: Writers and others who are using the ChatGPT desktop app on their Windows or Mac computers are finding that the chatbot is easier to integrate with more applications.

ChatGPT’s Advanced Voice Mode, for example, can now work with many more apps on the desktop, including Apple Notes and Quip.

Kevin Weil, chief product officer, OpenAI, indicates making app integration easier is part of an overall plan to make it virtually effortless later this year to enable ChatGPT to work with those apps as an autonomous agent.

*Microsoft’s Copilot to Feature More AI Engines in 2025: Writer Supreeth Koundinya reports that users of Microsoft Copilot will be able to power the app with competitors to ChatGPT this year.

Observes Koundinya: “This move stems from an attempt to reduce costs and diversify the underlying AI models. The company is also working on integrating its own models into 365 Copilot.”

As always, the more AI engines competing in the AI space, the better – cost-wise and performance-wise – for writers and others.

*2025: The Year of AI Agents: Add Time Magazine to the chorus of prognosticators predicting that AI agents – autonomous AI programs that will perform increasingly complex tasks for you – will become a thing this year.

Observes lead writer Tharin Pillay: “In October, Anthropic gave its AI model Claude the ability to use computers—clicking, scrolling and typing—but this may be just the start.

“Agents will be able to handle complex tasks like scheduling appointments and writing software, experts say.”

*Worth a Gander: 300+ Real-World Use Cases for AI: Writers and others still not convinced that AI is poised to remake the world may want to take a gander at this new report from Google.

It details 321 different applications of AI that are already in use by some of the world’s top businesses – with an emphasis on AI agent implementations.

Observes Brian Hall, vice president, product marketing, Google Cloud “In our work with customers, we see their teams are increasingly focused on improving productivity, automating processes and modernizing the customer experience.

“These aims are now being achieved through the AI agents they’re developing in six key areas: customer service, employee empowerment, code creation, data analysis, cybersecurity and creative ideation and production.”

*AI Big Picture: Study on AI Use by Businesses May Overlook Writing Apps: A new report from Vellum – a provider of AI app builder services – finds that 25% of small-to-large businesses have implemented AI.

But that percentage may be on the low side.

The reason: Vellum surveyed 1,250+ AI developers and builders – people who build AI systems from the ground-up — to formulate its estimate.

Missing from its survey, for example, may be all those other businesses that have simply integrated turn-key, cloud AI – such as ChatGPT, Anthropic Claude and Google Gemini — into their operations.

Such AI — and similar — can be ‘implemented’ with a simple, monthly subscription.

Observes writer Taryn Plumb regarding Vellum’s take: “This seems to indicate that many enterprises have not yet identified viable use cases for AI, keeping them — at least for now — in a pre-build holding pattern.”

Perhaps.

But it’s tough to imagine that most businesses – small or large — have not at least considered that AI like ChatGPT can be onboarded in a few days.

Essentially: It’s fairly easy for a business owner with 50 employees, for example, to imagine giving each employee a $20/month subscription to ChatGPT.

And it’s fairly easy to imagine that every one of those employees will be able to auto-write every email they send at the level of a world-class writer – with simply a few weeks of light training.

Share a Link:  Please consider sharing a link to https://RobotWritersAI.com from your blog, social media post, publication or emails. More links leading to RobotWritersAI.com helps everyone interested in AI-generated writing.

–Joe Dysart is editor of RobotWritersAI.com and a tech journalist with 20+ years experience. His work has appeared in 150+ publications, including The New York Times and the Financial Times of London.

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