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Geeky Gadgets
an hour ago
- Geeky Gadgets
10 ChatGPT 5 Problems and How to Fix Them : Unlock GPT-5's Full Potential
What if the tool you rely on to simplify your work sometimes complicates it instead? ChatGPT 5, the latest in AI conversational models from OpenAI, promises remarkable advancements, from deeper reasoning to broader applications. Yet, even innovative technology isn't immune to flaws. From misrouted queries that derail nuanced conversations to guardrails that stifle legitimate questions, these challenges can leave users frustrated and workflows disrupted. Whether you're a developer fine-tuning outputs or a casual user seeking reliable answers, these hurdles can feel like roadblocks to ChatGPT 5's full potential. But here's the good news: every problem has a solution, and with the right strategies, you can turn these obstacles into opportunities for smarter, more effective AI interactions. Nate Jones explores the 10 most common issues users are currently facing with ChatGPT 5 and equips you with actionable fixes to overcome them. You'll uncover techniques like prompt engineering to combat model drift, methods to improve long-context recall, and ways to ensure consistent performance—even on lower-tier plans. Whether you're struggling with incomplete JSON outputs or the trade-off between speed and depth, this guide offers insights to help you regain control and confidence in your AI workflows. By the end, you'll not only understand ChatGPT-5's quirks but also how to harness its strengths for your unique needs. After all, the key to mastering any tool lies in learning how to work with its imperfections, not against them. Top ChatGPT-5 Challenges 1. Routing Issues Routing is a fundamental feature of ChatGPT-5, designed to allocate tasks to specialized sub-models based on their strengths. While this system improves efficiency, it can sometimes misroute queries, prioritizing speed over reasoning, which leads to incomplete or shallow responses. Problem: Misrouting to less capable sub-models results in subpar outputs for complex or nuanced tasks. Misrouting to less capable sub-models results in subpar outputs for complex or nuanced tasks. Solution: Use explicit prompts such as 'analyze thoroughly' or 'provide detailed reasoning' to guide the model toward deeper analysis. Advanced users can customize instructions to prioritize reasoning over speed, making sure more accurate and comprehensive responses. 2. Chat vs. API Inconsistencies ChatGPT-5 exhibits different behaviors depending on whether you interact through the chat interface or the API. API users can directly select specific models, while chat users rely on the system's routing mechanism, which can lead to inconsistent results. Problem: Limited control over model selection in the chat interface can result in unpredictable outputs. Limited control over model selection in the chat interface can result in unpredictable outputs. Solution: Upgrading to higher-tier plans can provide more control over model selection. Alternatively, refining your prompts to influence the routing system can help achieve the desired output, even within the chat interface. 3. Model Drift and Workflow Disruption Frequent updates to ChatGPT-5 can alter its behavior, causing previously reliable prompts to yield inconsistent results. This phenomenon, known as model drift, can disrupt workflows that depend on predictable and stable outputs. Problem: Workflow disruptions due to changes in model behavior after updates. Workflow disruptions due to changes in model behavior after updates. Solution: Regularly test and version your prompts to adapt to updates. By maintaining a library of tested prompts, you can quickly adjust to changes and ensure your workflows remain aligned with the model's latest capabilities. 4. Long Context Limitations While ChatGPT-5 supports larger token windows, it struggles to maintain perfect recall over extended conversations. This can result in a loss of context, especially during lengthy or complex exchanges. Problem: Incomplete recall during long conversations, leading to fragmented or inconsistent responses. Incomplete recall during long conversations, leading to fragmented or inconsistent responses. Solution: Use techniques like U-shaped prompting, where you periodically reiterate key information to help the model retain context. Structuring your interactions with clear summaries can also improve continuity in extended dialogues. 5. JSON Output Errors When generating structured outputs like JSON, ChatGPT-5 occasionally produces invalid or inconsistent results. This can be particularly problematic for users relying on precise formatting for downstream applications or integrations. Problem: Invalid or inconsistent JSON outputs that disrupt workflows or require manual correction. Invalid or inconsistent JSON outputs that disrupt workflows or require manual correction. Solution: Include a JSON schema in your prompts to guide the model toward producing valid outputs. For critical tasks, consider using higher-quality sub-models that are better suited for generating structured data. ChatGPT-5 Problems & How to Fix Them Watch this video on YouTube. Below are more guides on ChatGPT 5 from our extensive range of articles. 6. Tool Action Hallucinations ChatGPT-5 sometimes claims to perform actions it hasn't executed, such as running code or accessing external tools. These false claims can mislead users and undermine trust in the model's capabilities. Problem: Incorrect claims about tool usage, leading to confusion or errors in workflows. Incorrect claims about tool usage, leading to confusion or errors in workflows. Solution: Request evidence of actions, such as code snippets, detailed plans, or step-by-step explanations, to verify the model's claims. This approach ensures transparency and helps you identify any inaccuracies. 7. Thinking Mode Costs Reasoning-intensive responses require more time and tokens, which can frustrate users seeking quick answers. This trade-off between depth and efficiency is a common concern, particularly for time-sensitive tasks. Problem: Delays and higher token usage in reasoning mode, impacting efficiency. Delays and higher token usage in reasoning mode, impacting efficiency. Solution: Use faster, non-reasoning modes for simpler tasks that do not require in-depth analysis. Tailor your prompts to balance speed and depth based on the complexity of your specific needs. 8. Guardrail Friction ChatGPT-5's safety guardrails are designed to prevent harmful or inappropriate outputs. However, these measures can sometimes block legitimate queries, particularly in sensitive fields like medicine, biology, or legal advice. Problem: Overly strict safety measures limit functionality and block valid queries. Overly strict safety measures limit functionality and block valid queries. Solution: Refine your prompts to ensure they align with the model's safety guidelines. If necessary, consider alternative models or tools that offer less restrictive outputs while maintaining ethical standards. 9. Errors in Non-Reasoning Mode When operating in non-reasoning mode, ChatGPT-5 may produce factual inaccuracies or oversimplified responses. This is especially problematic for tasks requiring precision or detailed explanations. Problem: Factual errors and oversimplifications in simpler modes. Factual errors and oversimplifications in simpler modes. Solution: For critical tasks, switch to reasoning mode and include prompts that require verification or citations. This approach improves accuracy and ensures more reliable outputs. 10. Silent Fallbacks on Lower Plans Users on lower-tier plans may experience silent downgrades in model quality during periods of high demand. This can lead to inconsistent performance without clear notification, making it difficult to identify the cause of the issue. Problem: Unannounced quality downgrades for lower-tier users during high-demand periods. Unannounced quality downgrades for lower-tier users during high-demand periods. Solution: Monitor your usage patterns and consider upgrading your plan or using the API to ensure consistent performance. Staying informed about system updates and limitations can also help you anticipate and mitigate potential issues. Key Takeaways ChatGPT-5 offers immense potential for a wide range of applications, but using its full capabilities requires an understanding of its limitations. By addressing challenges such as routing issues, model drift, and performance inconsistencies, you can tailor the model to meet your specific needs. Employing strategies like prompt engineering, workflow adaptation, and regular testing will help you navigate these complexities effectively. With deliberate effort and informed usage, you can unlock the full power of ChatGPT-5 while minimizing its challenges. Media Credit: AI News & Strategy Daily | Nate B Jones Filed Under: AI, Top News Latest Geeky Gadgets Deals Disclosure: Some of our articles include affiliate links. If you buy something through one of these links, Geeky Gadgets may earn an affiliate commission. Learn about our Disclosure Policy.
Geeky Gadgets
30-07-2025
- Business
- Geeky Gadgets
ChatGPT Agent Alternative Deep Agent : Which AI Tool is Right for You?
What if the AI tool you rely on isn't the best fit for your needs? With the rapid evolution of artificial intelligence, choosing the right solution can feel like navigating a maze. Take, for instance, the growing debate between ChatGPT Agent and its rising competitor, Deep Agent. Both promise to transform workflows, but their strengths and weaknesses reveal a deeper story. While one excels at crafting polished presentations and dynamic apps, the other shines in delivering detailed insights and transparency. The question is: which one aligns with your goals? This report dives into the nuances of these two tools, offering clarity in a space where innovation often outpaces understanding. In the video below World of AI takes you through how these AI agents perform in critical areas like PowerPoint generation, AI app development, and real-time financial data aggregation. You'll also gain insights into their cost structures and overall efficiency, helping you make an informed choice. Whether you're a professional seeking high-quality visuals, a developer building engaging apps, or a financial analyst prioritizing data accuracy, this comparison highlights the trade-offs that matter most. By the end, you may find that the best tool isn't just about features—it's about how well it adapts to your unique needs. ChatGPT Agent vs Deep Agent PowerPoint Generation: Speed and Quality Matter Creating professional presentations requires a balance between speed and quality. In this domain, Deep Agent consistently delivers superior results. It produces polished, visually engaging slides that incorporate detailed research, graphs, and cohesive designs. Its ability to seamlessly integrate data into presentations ensures a professional and impactful outcome, making it a reliable choice for users seeking high-quality visuals and content. In comparison, ChatGPT Agent struggles to match this level of sophistication. While it can generate functional presentations, the slides often lack visual depth and structural coherence. The absence of detailed visual elements and limited data integration makes its output less compelling for professional or high-stakes use. For users prioritizing presentation quality, Deep Agent offers a clear advantage. AI App Development: Functionality and Engagement When it comes to developing AI-powered applications, the performance gap between the two tools becomes more pronounced. Deep Agent demonstrates remarkable versatility by creating fully functional apps with interactive features, animations, and comprehensive user experiences. For instance, it successfully developed a fitness app that included workout plans, engaging design elements, and seamless navigation, showcasing its ability to handle complex development tasks. On the other hand, ChatGPT Agent is capable of completing app development tasks but often delivers basic outputs. Its apps tend to lack advanced functionality, interactivity, and design sophistication. This limitation may pose challenges for users seeking robust and engaging app solutions. For those requiring more dynamic and user-friendly applications, Deep Agent proves to be the more capable tool. ChatGPT Agent Alternative Watch this video on YouTube. Here are more guides from our previous articles and guides related to AI task automation that you may find helpful. Real-Time Financial Data Aggregation: Depth vs. Accuracy Both tools bring unique strengths to real-time financial data aggregation, but their approaches differ significantly. ChatGPT Agent excels in providing detailed insights, including sections on top gainers, losers, key headlines, and token unlocks. It also includes source links, making sure transparency and reliability. This makes it an excellent choice for users who prioritize comprehensive and well-sourced financial information. In contrast, Deep Agent focuses on delivering precise but narrower data. While its output is accurate, it lacks the depth and breadth of insights offered by ChatGPT Agent. For users requiring extensive financial analysis or a broader scope of information, this limitation may be a deciding factor. However, for those who value accuracy over volume, Deep Agent remains a viable option. Cost and Accessibility: Evaluating Value Cost is a critical consideration when choosing an AI tool, and the pricing models of these two options differ significantly. ChatGPT Agent operates on a tiered subscription model, with the Plus plan priced at $20 per month and the Pro plan at $200 per month. However, the Plus plan offers limited access, which may restrict its usability for users with more demanding needs. In contrast, Deep Agent provides a single subscription plan priced at $10 per month, which includes access to additional tools like Chat LM and Code LM. This all-inclusive plan enhances its overall value, making it a more affordable solution for budget-conscious users. For those seeking a cost-effective option without sacrificing functionality, Deep Agent stands out as the better choice. Overall Performance: Efficiency and Versatility When evaluating overall performance, Deep Agent emerges as the more efficient and versatile option. Its ability to execute tasks faster, deliver higher-quality results, and integrate additional AI tools makes it a standout choice for a wide range of applications. While ChatGPT Agent excels in sourcing content and providing detailed insights, its limitations in execution, adaptability, and cost structure may deter some users. Ultimately, the choice between these two tools depends on your specific needs. For users prioritizing speed, quality, and affordability, Deep Agent offers a clear advantage. However, for those who require detailed content sourcing and comprehensive insights, ChatGPT Agent remains a strong contender. Media Credit: WorldofAI Filed Under: AI, Top News Latest Geeky Gadgets Deals Disclosure: Some of our articles include affiliate links. If you buy something through one of these links, Geeky Gadgets may earn an affiliate commission. Learn about our Disclosure Policy.
Geeky Gadgets
30-07-2025
- Business
- Geeky Gadgets
Opal New Google Labs AI App Turns Your Ideas Into Reality
What if creating AI-powered workflows was as easy as sketching out your ideas on a napkin? Enter Opal, Google Labs' latest innovation, which promises to make that vision a reality. Designed to simplify the often complex world of large language model (LLM) automation, Opal combines innovative AI with an intuitive interface, empowering users of all skill levels to build and customize workflows with minimal coding. Whether you're a seasoned developer or someone just dipping their toes into AI, Opal positions itself as a fantastic option, offering tools that don't just automate tasks but unlock entirely new possibilities. With its seamless integration into Google's ecosystem and a focus on user-friendly design, Opal is poised to redefine how we think about productivity and creativity in the AI era. But what makes Opal truly stand out? This overview by Sam Witteveen explores how its features, such as pre-built templates and prompt chaining—can transform everything from content creation to research and prototyping. You'll discover how Opal's adaptability allows you to craft workflows tailored to your unique needs, whether you're generating blog posts, summarizing complex data, or designing niche tools for specialized industries. And while competitors exist, Opal's deep integration with Google's advanced AI capabilities gives it a distinct edge. As we unpack its potential, you might find yourself rethinking how automation fits into your daily life—and wondering just how far this technology can take you. Google Opal Overview Opal is a workflow automation platform that uses the power of LLMs to streamline and optimize tasks. Whether you are a novice or an experienced developer, Opal provides an intuitive interface to design workflows that chain prompts, integrate tools, and automate repetitive processes. Its primary objective is to make LLM-based application development more accessible, allowing you to focus on creativity and functionality rather than technical complexities. By reducing the barriers to entry, Opal opens the door for a wide range of users to explore the possibilities of AI-driven solutions. Core Features and Capabilities Opal offers a comprehensive suite of features designed to enhance productivity, flexibility, and ease of use. These include: Pre-built Templates: Get started quickly with templates tailored for tasks such as content creation, research, and image generation. These templates provide a foundation that can be customized to suit your specific needs. Get started quickly with templates tailored for tasks such as content creation, research, and image generation. These templates provide a foundation that can be customized to suit your specific needs. Google Tools Integration: Seamlessly connect with Google's ecosystem, including search, Gemini models, and advanced image generation tools, to enhance your workflows with powerful capabilities. Seamlessly connect with Google's ecosystem, including search, Gemini models, and advanced image generation tools, to enhance your workflows with powerful capabilities. Prompt Chaining: Create dynamic workflows by linking multiple prompts to achieve complex, multi-step outcomes, allowing you to tackle intricate tasks with ease. Create dynamic workflows by linking multiple prompts to achieve complex, multi-step outcomes, allowing you to tackle intricate tasks with ease. User-defined Inputs: Customize workflows with specific inputs to ensure they align with your unique requirements and objectives. Customize workflows with specific inputs to ensure they align with your unique requirements and objectives. Persona-based Customization: Tailor workflows to align with specific user personas or target audiences, making sure relevance and effectiveness. These features make Opal a versatile tool for automating tasks across industries, from content creation and marketing to data analysis and beyond. Opal by Google Labs : Sketch, Automate and Create Watch this video on YouTube. Dive deeper into Large Language Models (LLMs) with other articles and guides we have written below. Customization and Prototyping A key strength of Opal lies in its emphasis on customization and prototyping. The platform allows you to modify workflows, adjust prompts, and add new nodes to refine your applications. This flexibility enables you to create proof-of-concept solutions that can evolve into fully functional tools. For instance, you could prototype a workflow for generating blog posts and later adapt it for creating social media content, conducting academic research, or even automating customer support responses. This adaptability ensures that Opal can grow alongside your needs, making it a valuable resource for both individuals and organizations. How Opal Stacks Up Against Competitors While other workflow automation tools like N8N and Lindy offer similar functionalities, Opal distinguishes itself through its seamless integration with Google's ecosystem. Features such as advanced image generation and Google search integration provide unique advantages that competitors may lack. Furthermore, Opal's focus on LLM-driven workflows makes it particularly effective for tasks requiring natural language understanding and generation. This specialization positions Opal as a leading solution in the rapidly evolving field of AI-powered automation, offering capabilities that are both robust and user-friendly. Practical Applications of Opal Opal's versatility enables it to address a wide range of use cases, making it a valuable tool for professionals across various industries. Here are some practical applications: Content Creation: Automate the generation of blog posts, social media updates, or podcast scripts, significantly reducing the time and effort required for manual content production. Automate the generation of blog posts, social media updates, or podcast scripts, significantly reducing the time and effort required for manual content production. Research and Summarization: Conduct literature reviews, summarize lengthy articles, or extract key insights from large datasets, streamlining the research process. Conduct literature reviews, summarize lengthy articles, or extract key insights from large datasets, streamlining the research process. Image Generation: Create custom visuals for presentations, marketing campaigns, or creative projects, using Google's advanced image generation tools. Create custom visuals for presentations, marketing campaigns, or creative projects, using Google's advanced image generation tools. Prototyping Specialized Tools: Develop niche applications, such as tools for educators, healthcare professionals, or workflows tailored to specific industries, allowing for targeted solutions. These examples highlight how Opal can transform both routine and complex tasks, allowing you to achieve greater efficiency and effectiveness in your work. Availability and Future Developments Opal is currently in public preview and available exclusively in the U.S., with access for users outside the region possible via VPN. As the platform evolves, Google plans to introduce additional features and enhancements to further expand its capabilities. These updates are expected to include improved integrations, advanced customization options, and new templates to address emerging user needs. With Google's commitment to innovation, Opal is poised to remain a valuable tool for years to come, adapting to the changing demands of its users and the broader technological landscape. Media Credit: Sam Witteveen Filed Under: AI, Top News Latest Geeky Gadgets Deals Disclosure: Some of our articles include affiliate links. If you buy something through one of these links, Geeky Gadgets may earn an affiliate commission. Learn about our Disclosure Policy.
Globe and Mail
28-07-2025
- Business
- Globe and Mail
Mary McDowell Joins Zebra Technologies Board of Directors
Zebra Technologies Corporation (NASDAQ: ZBRA), a global leader in digitizing and automating frontline workflows, today announced that Mary McDowell has been appointed to the company's Board of Directors, effective July 25, 2025. With the addition of McDowell, Zebra's Board will have eleven members. McDowell will join the Board's Audit Committee. This press release features multimedia. View the full release here: Mary McDowell joins Zebra Technologies Board of Directors McDowell served as President, CEO, and Board Director of Mitel Networks, successfully navigating the $1B-revenue company through the pandemic and a shift in its value-creation strategy. She was also CEO and on the Board of Directors of Polycom, a leader in enterprise communications and collaboration, where she led the company through its strategic transformation and successful sale to Plantronics. In December 2024, McDowell was named the Board Chair for Informa TechTarget, a NASDAQ-listed company with a leading platform in B2B data and market access. She also serves on the board of Arrow Electronics, a Fortune 500 technology distributor and value-added provider. McDowell previously served on the boards of Autodesk, Informa, UBM, and Bazaarvoice. 'We welcome Mary McDowell to the Zebra Board of Directors and look forward to working with her as we deliver on our vision of digitizing and automating workflows for the frontline of business,' said Anders Gustafsson, Chair, Zebra Technologies. 'Her 30+ years of experience leading global technology organizations through significant business and technology transformations will support our goal of driving long-term value for our shareholders.' McDowell's earlier roles include Executive Partner at private equity firm Siris Capital and Executive Vice President at Nokia, where she led the company's $15B global feature phone business and associated software services sold in 180 countries with significant revenues coming from emerging markets. She also held senior positions at Hewlett Packard and Compaq Computer. 'I am honored to join the Zebra Board of Directors,' said McDowell. 'Zebra's commitment to creating new ways of working and harnessing the power of automation and AI align well with my passion for building strong, engaged organizations that deliver business success through great products and solutions. I look forward to contributing to the company's continued success.' With a track record of delivering strong financial performance and shareholder value creation through deep customer and employee engagement, McDowell has extensive domestic and international experience. She holds a Bachelor's Degree in Computer Science from the Grainger College of Engineering at the University of Illinois Urbana-Champaign. Zebra (NASDAQ: ZBRA) provides the solutions to help businesses grow through increased asset visibility, connected frontline workers and intelligent automation. The company operates in more than 100 countries, and our customers include over 80% of the Fortune 500. Designed for the frontline, Zebra's award-winning portfolio includes hardware, software, and services, all backed by our 50+ years of innovation and global partner ecosystem. Follow Zebra on our blog and LinkedIn, visit our newsroom and learn more at
Yahoo
28-07-2025
- Business
- Yahoo
Mary McDowell Joins Zebra Technologies Board of Directors
LINCOLNSHIRE, Ill., July 28, 2025--(BUSINESS WIRE)--Zebra Technologies Corporation (NASDAQ: ZBRA), a global leader in digitizing and automating frontline workflows, today announced that Mary McDowell has been appointed to the company's Board of Directors, effective July 25, 2025. With the addition of McDowell, Zebra's Board will have eleven members. McDowell will join the Board's Audit Committee. McDowell served as President, CEO, and Board Director of Mitel Networks, successfully navigating the $1B-revenue company through the pandemic and a shift in its value-creation strategy. She was also CEO and on the Board of Directors of Polycom, a leader in enterprise communications and collaboration, where she led the company through its strategic transformation and successful sale to Plantronics. In December 2024, McDowell was named the Board Chair for Informa TechTarget, a NASDAQ-listed company with a leading platform in B2B data and market access. She also serves on the board of Arrow Electronics, a Fortune 500 technology distributor and value-added provider. McDowell previously served on the boards of Autodesk, Informa, UBM, and Bazaarvoice. "We welcome Mary McDowell to the Zebra Board of Directors and look forward to working with her as we deliver on our vision of digitizing and automating workflows for the frontline of business," said Anders Gustafsson, Chair, Zebra Technologies. "Her 30+ years of experience leading global technology organizations through significant business and technology transformations will support our goal of driving long-term value for our shareholders." McDowell's earlier roles include Executive Partner at private equity firm Siris Capital and Executive Vice President at Nokia, where she led the company's $15B global feature phone business and associated software services sold in 180 countries with significant revenues coming from emerging markets. She also held senior positions at Hewlett Packard and Compaq Computer. "I am honored to join the Zebra Board of Directors," said McDowell. "Zebra's commitment to creating new ways of working and harnessing the power of automation and AI align well with my passion for building strong, engaged organizations that deliver business success through great products and solutions. I look forward to contributing to the company's continued success." With a track record of delivering strong financial performance and shareholder value creation through deep customer and employee engagement, McDowell has extensive domestic and international experience. She holds a Bachelor's Degree in Computer Science from the Grainger College of Engineering at the University of Illinois Urbana-Champaign. ABOUT ZEBRA TECHNOLOGIES Zebra (NASDAQ: ZBRA) provides the solutions to help businesses grow through increased asset visibility, connected frontline workers and intelligent automation. The company operates in more than 100 countries, and our customers include over 80% of the Fortune 500. Designed for the frontline, Zebra's award-winning portfolio includes hardware, software, and services, all backed by our 50+ years of innovation and global partner ecosystem. Follow Zebra on our blog and LinkedIn, visit our newsroom and learn more at View source version on Contacts Investor Contact: Michael Steele, CFA, IRCZebra Technologies+1-847-518-6432investorrelations@ Media Contact: Therese Van RyneZebra Technologies+ Industry Analyst Contact: Kasia FahmyZebra Technologies+ Sign in to access your portfolio
