1,517 Matching Annotations
  1. Last 7 days
    1. Współautorka benchmarku OneRuler: nie pokazaliśmy wcale, że język polski jest najlepszy do promptowania
      • Media circulated a claim that Polish language is best for prompting, but this was not a conclusion from the OneRuler study.
      • OneRuler is a multilingual benchmark testing how well language models process very long texts in 26 languages.
      • Models performed on average best with Polish, but differences compared to English were small and not explained.
      • Polish media prematurely concluded Polish is best for prompting, which the study's authors did not claim or investigate.
      • The benchmark tested models on finding specific sentences in long texts, akin to CTRL+F, a function AI models inherently lack.
      • Another task involved listing the most frequent words in a book; models often failed when asked to acknowledge if an answer was not present.
      • Performance dropped likely because the task required full context understanding, not just text searching.
      • Different books were used per language (e.g. Polish used "Noce i dnie," English used "Little Women"), impacting the fairness of comparisons.
      • The choice of books was based on expired copyrights, which influenced the results.
      • There is no conclusive evidence from this benchmark that Polish is superior for prompting due to multiple influencing factors.
      • No model achieved 100% accuracy, serving as a caution about language models' limitations; outputs should be verified.
      • Researchers advise caution especially when using language models for sensitive or private documents.
      • The OneRuler study was reviewed and presented at the CoLM 2025 conference.
    1. For instance, a recent analysis by Epoch AI of the total training cost of AI models estimated that energy was a marginal part of total cost of AI training and experimentation (less than 6% in the case of all 4 frontier AI models analyzed), and a recent analysis by Dwarkesh Patel and Romeo Dean estimated that power generation represents roughly 7% of a datacenter’s cost.

      Which paper or article from Romeo Dean and Dwarkesh patel?

    1. While closed-circuit cooling systems (i.e. where all of the water is recycled and none of it evaporates)[33] are technically feasible, they are more costly and therefore less common.

      This is description is how i understand it too, but the link does not seem to say this - it refers to open loop being about cooling a room, and closed loop as a sort of targetted cooling instead.

    2. They are very geographically concentrated - only 32 countries have data centers, and nearly half of them are in the United States. The state of Virginia has the highest density of data centers globally - it is home to almost 35% of all hyperscale data centers worldwide.

      This is a really useful stat. You need a specific definition of datacentre, but it's still handy.

    1. This transition is signaled by focused efforts from several major scientists and technology entities. Meta Chief AI Scientist Yann LeCun has emphasized his intent to pursue world models, while Fei-Fei Li’s World Labs has released its Marble model publicly. Concurrently, Google is testing its Genie models, and Nvidia is developing its Omniverse and Cosmos platforms for physical AI.

      Various examples of world model work: Nex to Yann LeCun. Fei-Fei Li World Labs w Marble model, Google has Genie models, Nvidia Omniverse and Cosmos.

    1. On Tuesday, news broke that he may soon be leaving Meta to pursue a startup focused on so-called world models, technology that LeCun thinks is more likely to advance the state of AI than Meta’s current language models.

      Yann LeCun says world models more promising. What are world models?

    1. n our latest findings, the share of respondents reporting mitigation efforts for risks such as personal and individual privacy, explainability, organizational reputation, and regulatory compliance has grown since we last asked about risks associated with AI overall in 2022.

      did they also ask whether those mitigation efforts negate gains in efficiency / innovation reported for AI?

    1. AI checking AI inherits vulnerabilities, Hays warned. "Transparency gaps, prompt injection vulnerabilities and a decision-making chain becomes harder to trace with each layer you add." Her research at Salesforce revealed that 55% of IT security leaders lack confidence that they have appropriate guardrails to deploy agents safely.

      abstracting away responsibilities is a dead-end. Over half of IT security think now no way to deploy agentic AI safely.

    2. When two models share similar data foundations or training biases, one may simply validate the other's errors faster and more convincingly. The result is what McDonagh-Smith describes as "an echo chamber, machines confidently agreeing on the same mistake." This is fundamentally epistemic rather than technical, he said, undermining our ability to know whether oversight mechanisms work at all.

      Similarity between models / training data creates an epistemic issue. Using them to control each other creates an echo chamber. Vgl [[Deontologische provenance 20240318113250]]

    3. Yet most organizations remain unprepared. When Bertini talks with product and design teams, she said she finds that "almost none have actually built it into their systems or workflows yet," treating human oversight as nice-to-have rather than foundational.

      Suggested that no AI using companies are actively prepping for AI Act's rules wrt human oversight.

    4. We're seeing the rise of a 'human on the loop' paradigm where people still define intent, context and accountability, whilst co-ordinating the machines' management of scale and speed," he explained.

      Human on the loop vs in

  2. Nov 2025
    1. While a plurality of respondents expect to see little or no effect on their organizations’ total number of employees in the year ahead, 32 percent predict an overall reduction of 3 percent or more, and 13 percent predict an increase of that magnitude (Exhibit 17). Respondents at larger organizations are more likely than those at smaller ones to expect an enterprise-wide AI-related reduction in workforce size, while AI high performers are more likely than others are to expect a meaningful change, either in the form of workforce reductions or increases.

      Interesting to see companies vary in their est of how AI will impact workforce. A third expects reduction (but not much, about 3%), 13% an increase (AI related hiring), 43% no change.

    2. with nearly one-third of all respondents reporting consequences stemming from AI inaccuracy (Exhibit 19).

      A third of respondents admit they've seen 'at least once' negative consequences of inaccurate output. That sounds low, as 100% will have been given hallucinations. So 1-in-3 doesn't catch them all before they run-up damage. (vgl Deloitte's work in Australia)

    3. The online survey was in the field from June 25 to July 29, 2025, and garnered responses from 1,993 participants in 105 nations representing the full range of regions, industries, company sizes, functional specialties, and tenures. Thirty-eight percent of respondents say they work for organizations with more than $1 billion in annual revenues. To adjust for differences in response rates, the data are weighted by the contribution of each respondent’s nation to global GDP.

      2k self selected respondents in 50% of nations. 4/10 are big corporates (over 1 billion USD annual revenue)

    4. McKinsey survey on AI use in corporations, esp perceptions and expectations. No actual measurements. I suspect it mostly measure the level of hype that respondents currently buy into.

    1. for - search prompt 2 - can an adult who has learned language experience pre-linguistic reality like an infant who hasn't learned language yet? - https://www.google.com/search?q=can+an+adult+who+has+learned+language+experience+pre-linguistic+reality+like+an+infant+who+hasn%27t+learned+language+yet%3F&sca_esv=869baca48da28adf&biw=1920&bih=911&sxsrf=AE3TifNnrlFbCZIFEvi7kVbRcf_q1qVnNw%3A1762660496627&ei=kBAQafKGJry_hbIP753R4QE&ved=0ahUKEwjyjouGluSQAxW8X0EAHe9ONBwQ4dUDCBA&uact=5&oq=can+an+adult+who+has+learned+language+experience+pre-linguistic+reality+like+an+infant+who+hasn%27t+learned+language+yet%3F&gs_lp=Egxnd3Mtd2l6LXNlcnAid2NhbiBhbiBhZHVsdCB3aG8gaGFzIGxlYXJuZWQgbGFuZ3VhZ2UgZXhwZXJpZW5jZSBwcmUtbGluZ3Vpc3RpYyByZWFsaXR5IGxpa2UgYW4gaW5mYW50IHdobyBoYXNuJ3QgbGVhcm5lZCBsYW5ndWFnZSB5ZXQ_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-K1A7IHCTItOC41Mi4xMbgHgcUBwgcHMzUuNDcuMsgHcQ&sclient=gws-wiz-serp - from - search prompt 1 - can we unlearn language? - https://hyp.is/Ywp_fr0cEfCqhMeAP0vCVw/www.google.com/search?sca_esv=869baca48da28adf&sxsrf=AE3TifMGTNfpTekWWBdYUA96_PTLS9T00A:1762658867809&q=can+we+unlearn+language?&source=lnms&fbs=AIIjpHxU7SXXniUZfeShr2fp4giZ1Y6MJ25_tmWITc7uy4KIegmO5mMVANqcM7XWkBOa06dn2D9OWgTLQfUrJnETgD74qUQptjqPDfDBCgB_1tdfH756Z_Nlqlxc3Q5-U62E4zbEgz3Bv4TeLBDlGAR4oTnCgPSGyUcrDpa-WGo5oBqtSD7gSHPGUp_5zEroXiCGNNDET4dcNOyctuaGGv2d44kI9rmR9w&sa=X&ved=2ahUKEwj4_LP9j-SQAxVYXUEAHVT8FfMQ0pQJegQIDhAB&biw=1920&bih=911&dpr=1 - to - search prompt 2 (AI) - can an adult who has learned language re-experience pre-linguistic phenomena like an infant with no language training? - https://hyp.is/m0c7ZL0jEfC8EH_WK3prmA/www.google.com/search?q=can+an+adult+who+has+learned+language+re-experience+pre-linguistic+phenomena+like+an+infant+with+no+language+training?&gs_lcrp=EgZjaHJvbWUyBggAEEUYOTIHCAEQIRiPAjIHCAIQIRiPAtIBCTQzNzg4ajBqN6gCALACAA&sourceid=chrome&ie=UTF-8&udm=50&ved=2ahUKEwjfrLqDm-SQAxWDZEEAHcxqJgkQ0NsOegQIAxAB&aep=10&ntc=1&mstk=AUtExfAG148GJu71_mSaBylQit3n4ElPnveGZNA48Lew3Cb_ksFUHUNmWfpC0RPR_YUGIdx34kaOmxS2Q-TjbflWDCi_AIdYJwXVWHn-PA6PZM5edEC6hmXJ8IVcMBAdBdsEGfwVMpoV_3y0aeW0rSNjOVKjxopBqXs3P1wI9-H6NXpFXGRfJ_QIY1qWOMeZy4apWuAzAUVusGq7ao0TctjiYF3gyxqZzhsG5ZtmTsXLxKjo0qoPwqb4D-0K-uW-xjkyJj0Bi45UPFKl-Iyabi3lHKg4udEo-3N4doJozVNoXSrymPSQbr2tdWcxw93FzdAhMU9QZPnl89Ty1w&csuir=1&mtid=WBYQaYfuHYKphbIPzYmKiAs

    1. Kommer den artificiella intelligensen att bli bättre på att tänka än den mänskliga? Kognitionsvetaren Peter Gärdenfors förklarar varför så inte är fallet.  Den mänskliga intelligensen består av en rad olika färdigheter och specialiteter som har förfinats under tusentals år. Mycket återstår innan den artificiella intelligensen kan mäta sig med det tänkande som inte bara människor utan även djur har. När vi förstår att vår intelligens är en bred palett av många olika förmågor ter sig tanken på att AI-tekniken trumfar oss i schack och kan skriva avancerade texter inte lika skrämmande. Utifrån ett brett forskningsunderlag förklarar Gärdenfors varför AI-tekniken inte kan och inte kommer att kunna tänka på samma sätt som människor och djur gör. »Peter Gärdenfors tilldelas Natur & Kulturs debattbokspris 2025 för att han fördjupar AI-debattens centrala begrepp och utmanar dess utgångspunkter. Med lätt språk och stabil lärdom blottlägger han tänkandets evolutionärt slipade mekanismer, och skärper bilden av vad intelligens är och vilken plats tekniken intar i vår digitala värld.« – Juryns motivering

      [[Kan AI tänka by Peter Gärdenfors]] via Sven Dahlstrand, dahlstrand.net Publ okt 2024 Seeks to define what thinking actually is, and how that plays out in other animals and humans. The 2nd part goes into sofrware systems and AI and how they work in comparison.

    1. AI is Making Us Work More
      • AI, intended to free workers, is causing longer work hours and increased pressure, spreading 996 culture to Western AI startups.
      • AI tools never tire, creating psychological pressure to constantly work and increasing feelings of guilt during rest.
      • Historical advances like lamps and bulbs extended work hours; AI similarly shifts "can work" into "should work."
      • Philosopher Byung-Chul Han's "Burnout Society" concept shows internalized self-discipline drives overwork, amplified by AI's "excess of positivity."
      • The hyper-productivity loop leads to burnout, reduced creativity, and diminishing returns despite increased effort.
      • Rest is framed as resistance and vital for innovation, which thrives on reflection, not constant activity.
      • The key challenge is adopting a healthy culture around AI use that avoids exploitation and preserves human well-being.
  3. Oct 2025
    1. Building fair AI systems is a continuous and deliberate effort. The model needs to be accurate but also maintain fairness, transparency and accountability.

      Learn practical strategies to design AI systems that avoid bias and ensure fairness. Discover techniques like diverse data, transparent algorithms, and robust evaluation pipelines to build ethical AI.

    2. AI systems are powerful tools-but if not built carefully, they can reinforce societal biases and make unfair decisions. Ensuring fairness and equity in AI is not just a technical challenge, but also a responsibility towards the development of ethical AI.

      Learn practical strategies to design AI systems that avoid bias and ensure fairness. Discover techniques like diverse data, transparent algorithms, and robust evaluation pipelines to build ethical AI.

    1. AWS Transcribe vs Deepgram vs Whisper, which speech-to-text solution should you choose for your voice enabled applications? Each platform is great in different areas like speed, accuracy, cost, and flexibility. This guide compares their strengths and limitations to help you pick the STT solution that fits your project and long-term goals.

      Compare AWS Transcribe, Deepgram, and Whisper for speech-to-text accuracy, pricing, integrations, and use cases. Find the best AI transcription service for your business.

    1. AI in WordPress development is changing the way websites are created and managed. It helps developers automate routine tasks, optimize performance, and deliver personalized user experiences. By integrating AI plugins or tools, WordPress sites can achieve faster design processes, smarter content generation, and overall improved functionality that enhances both visitor engagement and development efficiency.

      Explore how AI in WordPress development is reshaping websites, automating content creation, enhancing user experience with chatbots, and optimizing performance plugins. Learn top AI integration strategies, plugins, and best practices for modern WordPress sites.

    1. Amazon Plans to Replace More Than Half a Million Jobs With Robots
      • Internal documents reviewed by The New York Times show Amazon plans to automate up to 75% of its operations in the coming years.
      • The company expects automation to replace or eliminate over 500,000 U.S. jobs by 2033, primarily in warehouses and fulfillment centers.
      • By 2027, automation could allow Amazon to avoid hiring around 160,000 new workers, saving about 30 cents per package shipped.
      • This strategy is projected to save $12.6 billion in labor costs between 2025 and 2027.
      • Amazon’s workforce tripled since 2018 to approximately 1.2 million U.S. employees, but automation is expected to stabilize or reduce future headcount despite rising sales.
      • Executives presented to the board that automation could let the company double sales volume by 2033 without needing additional hires.
      • Amazon’s Shreveport, Louisiana warehouse serves as the model for the future: it operates with 25% fewer workers and about 1,000 robots.
      • A new facility in Virginia Beach and retrofitted older ones like Stone Mountain, Georgia, are following this design, which may shift employment toward more temporary and technical roles.
      • The company is instructing staff to use softer language—such as “advanced technology” or “cobots” (collaborative robots)—instead of terms like “AI” or “robots,” to ease concerns about job loss.
      • Amazon has begun planning community outreach initiatives (parades, local events) to offset the reputational risks of large-scale automation.
      • The company has denied that the documents represent official policy, claiming they reflect the views of one internal group, and emphasized ongoing seasonal hiring (250,000 roles for holidays).
      • Analysts suggest this plan could serve as a blueprint for other major employers, including Walmart and UPS, potentially reshaping U.S. blue‑collar job markets.
      • The automation push continues a trajectory started with Amazon’s $775 million acquisition of Kiva Systems in 2012, which introduced mobile warehouse robots that revolutionized internal logistics.
      • Recent innovations include robots like Blue Jay, Vulcan, and Proteus, aimed at performing tasks such as sorting, picking, and packaging with minimal human oversight.
      • Long-term, Amazon may require fewer warehouse workers but more robot technicians and engineers, signaling a broader shift in labor type rather than total employment.
    1. What you’re doing: Turning one-off prompts into reusable systems.Once you’ve perfected a workflow, you have a proven recipe. Now you can decide how to operationalise it. There are three options:Create a Prompt Template when you want to use it regularly for personal reuse onlyBuild a Custom GPT or Bot when you want to share a task-specific workflow with a team for cross-team quality and efficiency gains Create an Automated Agent when you want to trigger the workflow automatically in certain conditions

      How to create reusable systems

    2. File format matters. Here’s the reliability ranking for how well AI reads different formats:.txt / .md — Minimal noise, clear structure (best)JSON / CSV — Great for structured dataDOCX — Fine if formatting is simpleDigital PDFs — Extraction can mix headers, footers, columnsPPTX — Text order can be unpredictableScanned PDFs / images — Worst; requires OCR, highly error-prone

      How AI reads file formats and what they are good for

    1. Introduction: AI is now recently everywhere but we still need humans

    1. Discover how computer vision in AI is transforming industries by giving machines the ability to “see” and understand the visual world. This guide explores its core technology, diverse applications from self-driving cars to healthcare, and future trends, all while emphasizing its profound impact on business and daily life.

      A deep dive into how computer vision and AI are transforming industries, from healthcare diagnostics and autonomous vehicles to retail and manufacturing. Learn core technologies, real‑world applications, and future trends for leveraging visual intelligence in your business.

  4. Sep 2025
    1. Deciding between AI vs traditional software isn’t easy. Businesses struggle to decide between reliability and innovation. Do you stick with proven, rule-based systems or invest in adaptive, data-driven AI? This blog breaks down the differences, advantages, and use cases so you can make the right choice for your business.

      Compare AI vs Traditional Software Development to see which delivers better ROI. Explore cost, scalability, adaptability & when each model suits your business best.

  5. resu-bot-bucket.s3.ca-central-1.amazonaws.com resu-bot-bucket.s3.ca-central-1.amazonaws.com
    1. Developed an end-to-end full-stack web application to help students locate nearby study spots, track study sessions, and create study groups.

      Include user metrics or feedback that demonstrate the app's effectiveness or popularity.

    2. Led the development of a Telegram Bot that parses natural language commands to allow fast, secure expense-splitting on Aptos blockchain directly in your group chat.

      Add details on user adoption rates or how this improved user experience or efficiency.

    3. Trained a PyTorch neural network to classify forehand vs backhand shot techniques based on player joint positions, achieving 87% test accuracy.

      Explain the significance of 87% accuracy in practical terms, such as its effect on performance analysis.

    4. Implemented an upload-to-review system with AWS S3 for uploads, Hypothes.is for in-line resume annotations, and version tracking via DynamoDB, driving fast and iterative peer reviews.

      Clarify how much faster the review process became due to this implementation.

    5. Developed a Discord bot to streamline collaborative resume reviews for 2,000+ students, eliminating cluttered review threads and combining both peer and AI-powered resume annotations directly in Discord.

      Quantify the reduction in time spent on reviews or improvement in review quality.

    6. Redesigned layout and fixed critical responsiveness issues on 10+ web pages using Bootstrap, restoring broken mobile views and ensuring consistent, functional interfaces across devices.

      Include metrics on user engagement or satisfaction post-redesign to highlight impact.

    7. Developed dashboards for an internal portal with .NET Core, C#, and jQuery, eliminating the need for 100+ complex spreadsheets and enabling 30+ executives to securely access operational, financial, and customer data.

      Add a statement on how this improved decision-making or efficiency for the executives.

    8. Spearheaded backend unit testing automation for the shift-bidding platform using xUnit, SQLite, and Azure CI/CD Pipelines, contributing 40+ tests, identifying logic errors, and increasing overall test coverage by 15%.

      Explain how the increased test coverage improved system reliability or reduced bugs.

    9. Automated monthly shift-bid data transfers into the company HR system for 700+ employees using C#, SQL, and Azure Functions, saving supervisors hours of manual entry each month.

      Quantify 'hours saved' to provide a clearer impact of your automation efforts.

    10. Led the development of an Agentic AI staff scheduling app with React, C#/.NET, and Azure OpenAI, automating schedule templates for 12,000+ monthly flights and ensuring compliance with a RAG Policy chatbot.

      Specify the percentage improvement in scheduling efficiency or time saved due to automation.

    1. Current intellectual property laws constitute an “anti-constitutional” barrier to the transformative potential of artificial intelligence (AI), systematically frustrating the explicit purpose of the Intellectual Property (IP) Clause.

      This article reports that Anthropic has agreed to pay out a $1.5 billion settlement for copyright violations while training their Claude AI tool on books found on the Internet. That works out to be about $3000 per book.

      The whole idea of books (at least nonfiction books) is that readers are supposed to learn from them. But now if actual learning from them takes place it's a $3000 charge!

      It used to be that to violate a copyright required copying, not merely training. What's more, in the USA the sole justification for government-enforced monopolies on intellectual property is Article I, Section 8, Clause 8 of the U.S. Constitution, which authorizes copyrights and patents only to "to promote the Progress of Science and useful Arts," and only "for limited Times," and only "to Authors and Inventors." By extending copyright duration to the "author's life plus 70 years," Congress flouted those restrictions, and this precedent further tramples them, by clearly impeding the progress of science and useful arts.

  6. resu-bot-bucket.s3.ca-central-1.amazonaws.com resu-bot-bucket.s3.ca-central-1.amazonaws.com
    1. Instructed 1,000+ students on manufacturing best practices, emphasizing safety and build quality.

      Quantify the impact of your instruction. Did it lead to fewer errors or higher quality projects? Provide metrics.

    2. Trained over 100 students every semester on the safety protocols and applicable use cases for all MakerSpace equipment including 3D printers(FDM/SLA), laser cutters, CNC Machines, thermal formers, hand/power tools.

      Include the impact of your training. Did it lead to improved safety records or student confidence?

    3. Developed python-based computer vision dice recognition application capable of detecting and logging results for multiple dice types (D4–D20).

      Mention the user base or potential applications of this project. Who would benefit from it?

    4. Created standards for employee software interaction, improved efficiency, reducing operation costs by 40%.

      Detail what specific standards were created. How did they lead to the 40% cost reduction? Be more specific.

    5. Revised, modularized, and updated old assembly program to a modern code base removing 22 detected bugs enabling future feature implementation.

      Explain how bug removal improved functionality or user experience. Provide examples of features enabled.

    6. Unified three isolated programs into one software solution utilizing Java, PHP, SQL(MySQL), and RESTful API, removing the need for paper communication digitizing employee work.

      Quantify the impact of digitizing work. How much time or cost was saved? Include specific metrics.

    7. Supported 45 project groups with project management including Project Charter, Scope, DOD, Stakeholder management, WBS/WBS dictionary, scrum ceremonies, risk assessment, Agile, lifecycle, and product handover.

      Clarify your role in project management. Did you lead or facilitate? Highlight your direct contributions.

    8. Planned and implemented creative projects following the school’s curriculum and objectives, improving students’ understanding of course material, resulting in an average of a letter grade improvement.

      Specify how you measured the improvement in understanding. Include metrics or feedback to enhance impact.

    1. for - consciousness, AI, Alex Gomez- Marin, neuroscience, hard problem of consciousness, nonmaterialism, materialism - progress trap - transhumanism - AI - war on conciousness

      Summary - Alex advocates - for a nonmaterialist perspective on consciousness and argues - that there is an urgency to educate the public on this perspective - due to the transhumanist agenda that could threaten the future of humanity - He argues that the problem of whether consciousness is best explained by materialism or not is central to resolving the threat posed by the direction AI takes - In this regard, he interprets that the very words that David Chalmers chose to articulate the Hard Problem of Consciousness reveals the assumption of a materialist reference frame. - He used a legal metaphor too illustrate his point: - When a lawyer poses three question "how did you kill that person" - the question is entrapping the accused . It already contains the assumption of guilt. - I would characterize his role as a scientist who practices authentic seeker of wisdom - will learn from a young child if they have something valuable to teach and - will help educate a senior if they have something to learn - The efficacy of timebinding depends on authenticity and is harmed by dogma

  7. resu-bot-bucket.s3.ca-central-1.amazonaws.com resu-bot-bucket.s3.ca-central-1.amazonaws.com
    1. Implemented an LLM chatbox for AI-assisted debugging, fulfilling the client's priority and enhancing the tool's functionality.

      Quantify the enhancement. How much did functionality improve? Provide metrics if available.

    2. Collaborated within a 6-person team in an Agile environment, delivering project milestones over 5 sprints and incorporating peer feedback through 360-degree reviews.

      Specify the outcomes of the project milestones. What was the impact on the client or team?

  8. Aug 2025
    1. Laravel is not just keeping up with AI, it is thriving with it. The future of Laravel is all about smarter builds, AI integration, and scalable architecture. This blog dives into what’s changing and why it matters now.

      Discover how AI is shaping the future of Laravel with real-world AI integrations, from chatbots and predictive analytics to cloud-native deployments and AI-assisted development workflows.

  9. resu-bot-bucket.s3.ca-central-1.amazonaws.com resu-bot-bucket.s3.ca-central-1.amazonaws.com
    1. •Delivered personalized bill reviews to identify cost-saving opportunities and increase customer satisfaction.

      Include specific savings amounts or percentage increases in customer retention due to these reviews.

    2. •Provided tailored mobile solutions by assessing customer needs and recommending optimal phone, plan, and accessory options.

      Quantify the increase in customer satisfaction or sales resulting from these tailored solutions.

    3. •Contributed to game development using Figma, ensuring engaging UI/UX design and adherence to project goals within a tight deadline.

      State how the UI/UX design improved user interaction or satisfaction rates.

    4. •Collaborated with a team to design and develop IntegrityXplorer, an interactive 'Choose Your Own Adventure' game focused on academic integrity.

      Include specific metrics on user engagement or feedback received post-launch.

    1. Companies have invested billions into AI, 95 percent getting zero return

      MIT report: 95% of companies see no profit from investments in generative AI, which amounted to approximately $35 billion.

      Most AI pilots have no measurable impact on company profits. Attempts to implement tools like ChatGPT into the workplace primarily increase the productivity of individual employees, not the earnings of the entire company.

  10. resu-bot-bucket.s3.ca-central-1.amazonaws.com resu-bot-bucket.s3.ca-central-1.amazonaws.com
    1. •Implemented over 6 different JUnit tests for each function future-proofing development and open-source contributions.

      Clarify how these tests contributed to the project's reliability or ease of future updates.

    2. •Utilized Java libraries and frameworks to create functions that allowed for recursive generation of the dice.

      Explain the significance of this feature—how does it enhance the application's functionality or user experience?

    3. •Developed standards for employee software interaction, reduced operating costs by 40%, improving functionality.

      Explain how reduced costs translated to benefits for the company (e.g., increased revenue, efficiency).

    4. •Unified three isolated programs into one software solution utilizing Java, PHP, SQL(MySQL), and RESTful API reducing user workload by up to 75%.

      Clarify the context of 'user workload' reduction—what tasks were simplified or eliminated?

    5. •Partnered with the professor, planned and implemented creative projects following the school’s curriculum and objectives, improving students’ understanding of course material.

      Specify how much student understanding improved (e.g., grades, feedback) to quantify impact.

    1. This blog discusses how to generate 3D images using AI using text prompts or 2D images. We discuss how to set up your system to AI-powered 3D image generation, including hardware and software requirements. You also get information on leading 3D AI tools like Meshy AI, Spline and more.

      Learn how to generate 3D images using AI models. This guide covers top tools and best practices to help designers and developers bring their 3D visions to life efficiently.

    1. for - youtube - BBC - AI2027 - Futures - AI - progress trap - AI - to AI2027 website - https://hyp.is/0VHJqH3cEfCm9JM_EB3ypQ/ai-2027.com/

      summary - This dystopian futures scenario is the brainchild of former OpenAI researcher Daniel Kokotajlo, - It is premised on human behavior in modernity including - confirmation bias of AI researchers - entrenched competing political ideologies that motivate an AI arms race - entrenched capitalist market behavior that motivates an AI arms race - AI becoming embodied, resulting in Artificially Embodied Artificial Intelligence (AEAI), posing the danger to humanity because it's no longer just talk, but action - Can it happen? The probability is not zero.We don't really understand the behavior of the AI LLM's we design, they are nonpredictable, and as we give them even greater power, that is a slippery slope - AI can become humanity's ultimate progress trap, which is ironic, because the technology that promises to be the most efficient of all, can become so efficient, it no longer need human beings - Remember Jerry Kaplan's book "Humans need not apply"? - https://hyp.is/o0lBFH3fEfC1QLfnLSs5Bg/www.youtube.com/watch?v=JiiP5ROnzw8 - This dystopian futures scenario goes further and explores the idea that "humans need not exist"!

      question - What about emulating climate change gamification of "Bend the Curve" of emissions? - Use the AI 2027 trajectory as a template and see how much real-life follows this trajectory - Just as we have the countdown to the https://climateclock.world/ ( 3 years and change remaining as of today) - perhaps we can have an AI 2027 clock? - What can we do to "bend the dystopian AI 2027 curve" AWAY from the dystopian future?

    1. This guide shows how to build an Agentic SaaS platform that pairs scalable cloud software with autonomous AI agents to learn and adapt. It covers core design principles, real-world use cases, and practical steps to future-proof your business. The focus is on enhancing user experience, boosting efficiency, and ensuring strong security through seamless AI integration.

      Learn how to build an agentic SaaS platform powered by autonomous AI systems capable of perceiving, planning, deciding, and acting. Explore architecture components, real-world use cases, and transformation strategies for intelligent SaaS.

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    1. Partner with clinicians, researchers, and cybersecurity/privacy officers to turn clinical pain-points into digital-health pilot ideas

      Specify the number of pilot ideas developed and their impact on patient care or efficiency.

    1. But won’t this stifle innovation, one might worry? Quite the opposite, we think. Europe's competitive advantage in AI is unlikely to arise from pouring hundreds of billions into building the largest foundational models. Instead, it will come from industrial adoption, effectively integrating GPAI into useful downstream applications–an approach that plays to Europe’s true strengths: rich data pools, world-class applied engineering capabilities and dynamic SMEs, which make up 99% of all businesses.

      This is an interesting angle - ease of adoption when the tech is "boring", and reduced risk

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    1. Developed a full-stack web application using with Flask serving a REST API with React as the frontend

      Remove 'using with' for clarity. Add impact metrics, such as user adoption rates or performance improvements.