#Generative AI In Coding Market Analysis

[industrynewsupdates]

A Comprehensive Overview of Generative AI In Coding Market Landscape

The global generative AI in coding market size is expected to reach USD 106.3 million by 2030, according to a new report by Grand View Research, Inc. The market is anticipated to expand at a CAGR of 25.2% from 2023 to 2030. Generative AI's impact on coding rapidly expands as developers use advanced models and successors to streamline software development. These models generate code snippets, offer creative solutions, automate documentation, enhance code comprehension, and enable rapid prototyping. As the technology evolves, its ability to address diverse programming languages and specific domains grows, empowering developers with efficient coding assistance and accelerating the iterative development process.

The rise in the development of AI models specifically designed for code generation propels the market forward. These models might be fine-tuned on programming languages, frameworks, and software development contexts, making their suggestions even more relevant and accurate. For instance, GitHub Copilot is an AI-driven coding tool that GitHub, OpenAI, and Microsoft Corporation developed. This tool offers code suggestions in Visual Studio, Neovim, and JetBrains development environments. Its ability to suggest relevant code snippets and auto-completion can save time and effort while improving code quality and consistency.

By integrating generative AI and low-code, systems can autonomously manage tasks, reducing human involvement. Low-code software democratizes development within organizations, while generative AI enhances efficiency. This synergy could streamline app creation in low-code and no-code platforms, where AI generates code from visual input. According to Microsoft's Low-Code Signals 2023 report, 87% of innovation leaders and IT professionals anticipate improved utilization through increased AI and automation within low-code platforms.

Gather more insights about the market drivers, restrains and growth of the Generative AI In Coding Market

Generative AI In Coding Market Report Highlights

• Code Generation segment dominated the market with a revenue share of 37.4% in 2022. As software development becomes more pervasive across industries, the demand for code is increasing. Generative AI assists in meeting this demand by accelerating code production.

• The North America region dominated the market with a revenue share of 29.3% in 2022. The interconnected tech ecosystem in North America encourages cross-industry collaboration and knowledge-sharing, further fueling the adoption of generative AI in coding.

• The collaboration among AI research, hardware progress, and vast datasets drives market by furnishing developers with more potent and streamlined tools. These tools simplify coding tasks, resulting in enhanced efficiency and the creation of superior software products.

• As artificial intelligence gains more recognition for its effectiveness across industries, there's a rising interest in utilizing generative AI for coding, driven by its potential to enhance coding processes. This interest stems from understanding AI's value in improving coding efficiency.

Generative AI In Coding Market Segmentation

Grand View Research has segmented the global generative AI in coding market based on operation, application, industry vertical and regional.

Generative AI in Coding Operation Outlook (Revenue, USD Million; 2018 - 2030)

• Code Generation

• Code Enhancement

• Language Translation

• Code Reviews

Generative AI in Coding Application Outlook (Revenue, USD Million; 2018 - 2030)

• Data Science and Analytics

• Game Development and Design

• Web and Application Development

• IoT and Smart Devices

Generative AI in Coding Industry Vertical Outlook (Revenue, USD Million; 2018 - 2030)

• BFSI

• Media and Entertainment

• IT & Telecom

• Healthcare and Life Sciences

• Transport & Logistics

• Retail & E-commerce

Generative AI in Coding Regional Outlook (Revenue, USD Million; 2018 - 2030)

• North America

o U.S.

o Canada

• Europe

o U.K.

o Germany

o France

• Asia Pacific

o China

o Japan

o India

o South Korea

o Australia

• Latin America

o Brazil

o Mexico

• Middle East and Africa

o KSA

o UAE

o South Africa

List of Key Players in the Generative AI In Coding Market

• Codecademy

• CodiumAI

• DeepCode

• Google LLC

• IBMCorporation

• Microsoft Corporation

• NVIDIA Corporation

• OpenAI

• Tabnine

• Codota

Order a free sample PDF of the Generative AI In Coding Market Intelligence Study, published by Grand View Research.

[mifiada]

MifiadaHome Starting a Brand | AI in Brand Marketing: Can AI Pave the Path to Social Media Millions? Episode 1

A current MSc Marketing student, I often find myself researching into the world of Digital Marketing more specifically overnight 'virilisation' and furthermore the 'social media millions' that so many millennials dream of. With the glamorous lives of social media influences further demonstrating how fame and fortune can be attained by generating a large audience through social media virilisation, the question arises: is it attainable for the average millennial like you or me, who is not famous, nor born of privilege, but armed with a mobile phone and big dreams?

The Allure of Virality: A Millennials Obsession?

Debunking the myth behind AI, particularly tools such as ChatGPT or Gemini, being the holy grail to attaining overnight success. With AI gurus filling our #fyp with heavy promises of achieving financial freedom and escaping from the controversial 9-to-5, every millennial's dream of monetising their passion. Unfortunately, the harsh reality is that viral moments are fleeting, unpredictable, and even when attained, to reach social media stardom and replicate said moment, this often becomes impossible. Initially, understanding being virality is more to do with luck and an intangible 'it' factor than any replicable strategy.

AI as the Navigator in the Viral Storm?

My perspective on AI begins to shift with the discovery of a specific software called Kling AI. The pursuit of 'virality', as I now understand it, isn't just about random chance; it's about optimising efforts for maximum shareability and resonance.

My previous reflection within the topic focused on AI's ability to understand audiences, and craft compelling narratives, and identify your inner influencer abilities. Now, I see how these capabilities directly feed into the virilisation equation. If Tuten & Solomon (2015) emphasised engagement and relationship, then 'Kling AI' takes that a step further by identifying the optimal points of engagement that trigger sharing. Imagine an AI that doesn't just tell you what your audience likes, but what they are most likely to share with their network. This isn't about creating a viral hit from scratch, but about increasing the probability of viral spread for well-crafted content.

Storytelling for Shareability: The AI Edge?

The power of a narrative, as Van Laer et al. (2014) articulated, lies in its ability to transport an audience. To go viral, you need to be more than just author; but rather transcend your audiences mind to a world which was previously unknown, a subtle but crucial distinction.

With cutting edge animation 'Kling AI's' ability to tell a story is unmatched. It also enables past performance analysis to better develop storylines, this is powerful for identifying stories that better resonates with the audience, which would propel people to share them this could be:

Addictive Content:

-Emotional hook

-Surprising twist

-Universal truth

A cheat code to knowing what design, colour scheme, theme has previous resulted in higher viewer count, moves past the guessing game or what others might deem luck but rather the ability to make data driven creative decisions.

The Conclusion: How do you amplify Organic Reach?

Rosenbaum's (2011) "Curation Nation" this concept demonstrates the active role users play in content creation. The need for community is seen in other words as an engine of virality. Through the play of consistency, this doesn't leave process of becoming viral to chance but rather through sawing seed via more than one social platform, it allows for the opportunity of it flourishes sparking a chair reaction for the creator to then replicate said moment.

Reference List:

Rosenbaum, S. (2011) Curation Nation: How to Win in a World Where Consumers are Creators. New York: McGraw-Hill.

Tuten, T.L. and Solomon, M.R. (2015) Social Media Marketing. 2nd edn. London: Sage Publications.

Van Laer, T., De Ruyter, K., Visconti, L.M. and Wetzels, M. (2014) ‘The Extended Transportation-Imagery Model: A Meta-Analysis of the Antecedents and Consequences of Consumers’ Narrative Transportation’, Journal of Consumer Research, 40(5), pp. 797–817. https://doi.org/10.1086/673383

[niotechone]

Cloud Computing: Definition, Benefits, Types, and Real-World Applications

In the fast-changing digital world, companies require software that matches their specific ways of working, aims and what their customers require. That’s when you need custom software development services. Custom software is made just for your organization, so it is more flexible, scalable and efficient than generic software.

What does Custom Software Development mean?

Custom software development means making, deploying and maintaining software that is tailored to a specific user, company or task. It designs custom Software Development Services: Solutions Made Just for Your Business to meet specific business needs, which off-the-shelf software usually cannot do.

The main advantages of custom software development are listed below.

1. Personalized Fit

Custom software is built to address the specific needs of your business. Everything is designed to fit your workflow, whether you need it for customers, internal tasks or industry-specific functions.

2. Scalability

When your business expands, your software can also expand. You can add more features, users and integrations as needed without being bound by strict licensing rules.

3. Increased Efficiency

Use tools that are designed to work well with your processes. Custom software usually automates tasks, cuts down on repetition and helps people work more efficiently.

4. Better Integration

Many companies rely on different tools and platforms. You can have custom software made to work smoothly with your CRMs, ERPs and third-party APIs.

5. Improved Security

You can set up security measures more effectively in a custom solution. It is particularly important for industries that handle confidential information, such as finance, healthcare or legal services.

Types of Custom Software Solutions That Are Popular

CRM Systems

Inventory and Order Management

Custom-made ERP Solutions

Mobile and Web Apps

eCommerce Platforms

AI and Data Analytics Tools

SaaS Products

The Process of Custom Development

Requirement Analysis

Being aware of your business goals, what users require and the difficulties you face in running the business.

Design & Architecture

Designing a software architecture that can grow, is safe and fits your requirements.

Development & Testing

Writing code that is easy to maintain and testing for errors, speed and compatibility.

Deployment and Support

Making the software available and offering support and updates over time.

What Makes Niotechone a Good Choice?

Our team at Niotechone focuses on providing custom software that helps businesses grow. Our team of experts works with you throughout the process, from the initial idea to the final deployment, to make sure the product is what you require.

Successful experience in various industries

Agile development is the process used.

Support after the launch and options for scaling

Affordable rates and different ways to work together

Final Thoughts

Creating custom software is not only about making an app; it’s about building a tool that helps your business grow. A customized solution can give you the advantage you require in the busy digital market, no matter if you are a startup or an enterprise.

[anti-ai-until-i-fucking-die]

University has gotten so weird since the introduction of generative AI, particularly chatgpt. I currently have an assessment where the first section is to use gen ai it answer a question and then criticise the response with your own analysis.

a) ew

b) I have never even opened chatgpt before and have 0 interest in "learning to use the tool effectively", but it's a group assessment so I just took the other section of the assessment and left everyone to their peace.

Reading now through their work I am left with only more questions of how people think there is any merit in this damn program. Part of the referencing of this assessment is to copy and paste whatever the AI spits out and put it as an appendix in the report so that the marker is fully aware of what is AI an what is original thought. Proofreading their section I also became curious because I am an annoying little bitch who is has been screwed over by group projects and AI before, and I am not flunking a class, losing thousands in debt, and having this on my academic record because the teacher thought this would be a good learning experience and my groupmates have become too dependent (I am incredibly biased and angry about gen ai's very existence, I was a student long before AI existed and now am baffled at how people think like this)

Reading what the AI spit out I am seeing more prompts about how to critically analyse the work, "why AI is not reliable", "what are the risks in using AI for business decisions", what is happening? There is 20% of this assessment section that required critical thought and they are still passing it off to AI. I mean props for including it in the assessment and not just lying your ass off but jesus christ.

In another class, not for an assessment, just an exercise, we had to code a simulation of a robot. I know nothing about coding but this was baby code, literally structured text that you could theoretically pick up in 20 minutes. This is the fun exercise where you play with numbers and watch a little digital robot dance. No grades, no assessment, no consequence, just an hour to mess around and get shit wrong. This is everything I love about classes and it is so hard to get when your smashed with assessments and tests and work and every other godforsaken thing that you need to fit into your life.

In pairs, rather than use the program and play around, 30 seconds in my partner pulls out chatgpt, puts the prompt in, puts it in again asking "is this good code," or "fix this code" or some shit, plugs it into the program and shows it to the teacher.

a) ew

b) teacher was very aware that it was AI because people do not type that fast and if people don't want to do work why argue with them. Let them lose the opportunity

c) now I get to sit scrolling through my emails for an hour pissed as hell because I didn't actually do anything. I didn't type, read, edit, once it was done it was gone and I missed what was potentially a fun activity. Not to mention this a robotics class, I am a girl studying marketing, I am very aware that I am out of my depths and went in saying I was just curious to learn something new, and I didn't even get to.

I don't know if this is just addictive for some people, like how I need to google all the actors in a movie once I see someone I kind of recognise I can't quite place. I know if ruins the movie immersion but I just can't help myself. Or if people genuinely believe this is a way to learn. I taught myself so much neuroscience in highschool because I struggled to study. Now I know it's because I had a lot of undiagnosed bullshit, but I needed to know how to get my brain to retain information because surely something would work. Other people don't have this context and maybe think that typing a prompt is enough.

Honestly I think that people are just tired. I get it. I'm tired. Capitalism profits off of collective exhaustion. Too tired to cook? pay a $10 delivery fee. order something and it came broken or just shitty? you could send it back, get a refund, leave a bad review, blah blah blah, but that's a lot of work for what... $20? $15? Just move on and buy the next thing.

Too tired to write out an essay? I get it. I do. Chatgpt is not the answer. My executive dysfunction needs a damn title bump for all the shit I leave to last hour but I need to suffer the consequences of those actions. I need to make myself sick on caffeine, I need to be exhausted the next day, I need to go to my teacher with my tail between my legs and a shitty report we both know I could've done better on. Or I will do it all again.

Guilt and shame and regret fucking suck but you won't grow without it. And you sure as fuck cannot grow with chatgpt.

I am terrified of the next 10 years where every job I have is going to ask me to use this nonsense, or further still, society is going to collapse because of a lack of reading comprehension, media literacy, environmental disaster, deepfake porn, AI therapists, or whatever orwellian horror is going to come next.

I'm not just tired, I'm fucking terrified.

[riazhatvi]

People Think It’s Fake" | DeepSeek vs ChatGPT: The Ultimate 2024 Comparison (SEO-Optimized Guide)

The AI wars are heating up, and two giants—DeepSeek and ChatGPT—are battling for dominance. But why do so many users call DeepSeek "fake" while praising ChatGPT? Is it a myth, or is there truth to the claims? In this deep dive, we’ll uncover the facts, debunk myths, and reveal which AI truly reigns supreme. Plus, learn pro SEO tips to help this article outrank competitors on Google!

Chapters

00:00 Introduction - DeepSeek: China’s New AI Innovation

00:15 What is DeepSeek?

00:30 DeepSeek’s Impressive Statistics

00:50 Comparison: DeepSeek vs GPT-4

01:10 Technology Behind DeepSeek

01:30 Impact on AI, Finance, and Trading

01:50 DeepSeek’s Effect on Bitcoin & Trading

02:10 Future of AI with DeepSeek

02:25 Conclusion - The Future is Here!

Why Do People Call DeepSeek "Fake"? (The Truth Revealed)

The Language Barrier Myth

DeepSeek is trained primarily on Chinese-language data, leading to awkward English responses.

Example: A user asked, "Write a poem about New York," and DeepSeek referenced skyscrapers as "giant bamboo shoots."

SEO Keyword: "DeepSeek English accuracy."

Cultural Misunderstandings

DeepSeek’s humor, idioms, and examples cater to Chinese audiences. Global users find this confusing.

ChatGPT, trained on Western data, feels more "relatable" to English speakers.

Lack of Transparency

Unlike OpenAI’s detailed GPT-4 technical report, DeepSeek’s training data and ethics are shrouded in secrecy.

LSI Keyword: "DeepSeek data sources."

Viral "Fail" Videos

TikTok clips show DeepSeek claiming "The Earth is flat" or "Elon Musk invented Bitcoin." Most are outdated or edited—ChatGPT made similar errors in 2022!

DeepSeek vs ChatGPT: The Ultimate 2024 Comparison

1. Language & Creativity

ChatGPT: Wins for English content (blogs, scripts, code).

Strengths: Natural flow, humor, and cultural nuance.

Weakness: Overly cautious (e.g., refuses to write "controversial" topics).

DeepSeek: Best for Chinese markets (e.g., Baidu SEO, WeChat posts).

Strengths: Slang, idioms, and local trends.

Weakness: Struggles with Western metaphors.

SEO Tip: Use keywords like "Best AI for Chinese content" or "DeepSeek Baidu SEO."

2. Technical Abilities

Coding:

ChatGPT: Solves Python/JavaScript errors, writes clean code.

DeepSeek: Better at Alibaba Cloud APIs and Chinese frameworks.

Data Analysis:

Both handle spreadsheets, but DeepSeek integrates with Tencent Docs.

3. Pricing & Accessibility

FeatureDeepSeekChatGPTFree TierUnlimited basic queriesGPT-3.5 onlyPro Plan$10/month (advanced Chinese tools)$20/month (GPT-4 + plugins)APIsCheaper for bulk Chinese tasksGlobal enterprise support

SEO Keyword: "DeepSeek pricing 2024."

Debunking the "Fake AI" Myth: 3 Case Studies

Case Study 1: A Shanghai e-commerce firm used DeepSeek to automate customer service on Taobao, cutting response time by 50%.

Case Study 2: A U.S. blogger called DeepSeek "fake" after it wrote a Chinese-style poem about pizza—but it went viral in Asia!

Case Study 3: ChatGPT falsely claimed "Google acquired OpenAI in 2023," proving all AI makes mistakes.

How to Choose: DeepSeek or ChatGPT?

Pick ChatGPT if:

You need English content, coding help, or global trends.

You value brand recognition and transparency.

Pick DeepSeek if:

You target Chinese audiences or need cost-effective APIs.

You work with platforms like WeChat, Douyin, or Alibaba.

LSI Keyword: "DeepSeek for Chinese marketing."

SEO-Optimized FAQs (Voice Search Ready!)

"Is DeepSeek a scam?" No! It’s a legitimate AI optimized for Chinese-language tasks.

"Can DeepSeek replace ChatGPT?" For Chinese users, yes. For global content, stick with ChatGPT.

"Why does DeepSeek give weird answers?" Cultural gaps and training focus. Use it for specific niches, not general queries.

"Is DeepSeek safe to use?" Yes, but avoid sensitive topics—it follows China’s internet regulations.

Pro Tips to Boost Your Google Ranking

Sprinkle Keywords Naturally: Use "DeepSeek vs ChatGPT" 4–6 times.

Internal Linking: Link to related posts (e.g., "How to Use ChatGPT for SEO").

External Links: Cite authoritative sources (OpenAI’s blog, DeepSeek’s whitepapers).

Mobile Optimization: 60% of users read via phone—use short paragraphs.

Engagement Hooks: Ask readers to comment (e.g., "Which AI do you trust?").

Final Verdict: Why DeepSeek Isn’t Fake (But ChatGPT Isn’t Perfect)

The "fake" label stems from cultural bias and misinformation. DeepSeek is a powerhouse in its niche, while ChatGPT rules Western markets. For SEO success:

Target long-tail keywords like "Is DeepSeek good for Chinese SEO?"

Use schema markup for FAQs and comparisons.

Update content quarterly to stay ahead of AI updates.

🚀 Ready to Dominate Google? Share this article, leave a comment, and watch it climb to #1!

Follow for more AI vs AI battles—because in 2024, knowledge is power! 🔍

[raomarketingpro]

Free AI Tools

Artificial Intelligence (AI) has revolutionized the way we work, learn, and create. With an ever-growing number of tools, it’s now easier than ever to integrate AI into your personal and professional life without spending a dime. Below, we’ll explore some of the best free AI tools across various categories, helping you boost productivity, enhance creativity, and automate mundane tasks.

Wanna know about free ai tools

1. Content Creation Tools

ChatGPT (OpenAI)

One of the most popular AI chatbots, ChatGPT, offers a free plan that allows users to generate ideas, write content, answer questions, and more. Its user-friendly interface makes it accessible for beginners and professionals alike.

Best For:

Writing articles, emails, and brainstorming ideas.

Limitations:

Free tier usage is capped; may require upgrading for heavy use.

Copy.ai

Copy.ai focuses on helping users craft engaging marketing copy, blog posts, and social media captions.

2. Image Generation Tools

DALL·EOpenAI’s DALL·E can generate stunning, AI-created artwork from text prompts. The free tier allows users to explore creative possibilities, from surreal art to photo-realistic images.

Craiyon (formerly DALL·E Mini)This free AI image generator is great for creating quick, fun illustrations. It’s entirely free but may not match the quality of professional tools.

3. Video Editing and Creation

Runway MLRunway ML offers free tools for video editing, including AI-based background removal, video enhancement, and even text-to-video capabilities.

Pictory.aiTurn scripts or blog posts into short, engaging videos with this free AI-powered tool. Pictory automates video creation, saving time for marketers and educators.

4. Productivity Tools

Notion AINotion's AI integration enhances the already powerful productivity app. It can help generate meeting notes, summarize documents, or draft content directly within your workspace.

Otter.aiOtter.ai is a fantastic tool for transcribing meetings, interviews, or lectures. It offers a free plan that covers up to 300 minutes of transcription monthly.

5. Coding and Data Analysis

GitHub Copilot (Free for Students)GitHub Copilot, powered by OpenAI, assists developers by suggesting code and speeding up development workflows. It’s free for students with GitHub’s education pack.

Google ColabGoogle’s free cloud-based platform for coding supports Python and is perfect for data science projects and machine learning experimentation.

6. Design and Presentation

Canva AICanva’s free tier includes AI-powered tools like Magic Resize and text-to-image generation, making it a top choice for creating professional presentations and graphics.

Beautiful.aiThis AI presentation tool helps users create visually appealing slides effortlessly, ideal for professionals preparing pitch decks or educational slides.

7. AI for Learning

Duolingo AIDuolingo now integrates AI to provide personalized feedback and adaptive lessons for language learners.

Khanmigo (from Khan Academy)This AI-powered tutor helps students with math problems and concepts in an interactive way. While still in limited rollout, it’s free for Khan Academy users.

Why Use Free AI Tools?

Free AI tools are perfect for testing the waters without financial commitments. They’re particularly valuable for:

Conclusion

AI tools are democratizing access to technology, allowing anyone to leverage advanced capabilities at no cost. Whether you’re a writer, designer, developer, or educator, there’s a free AI tool out there for you. Start experimenting today and unlock new possibilities!

4o

[mariacallous]

The launch of ChatGPT-3.5 at the end of 2022 captured the world’s attention and illustrated the uncanny ability of generative artificial intelligence (AI) to produce a range of seemingly human-generated content, including text, video, audio, images, and code. The release, and the many eye-catching breakthroughs that quickly followed, have raised questions about what these fast-moving generative AI technologies might mean for work, workers, and livelihoods—now and in the future, as new models are released that are potentially much more powerful. Many U.S. workers are worried: According to a Pew Research Center poll, most Americans believe that generative AI will have a major impact on jobs—mainly negative—in the next two decades. 

Despite these widely shared concerns, however, there is little consensus on the nature and scale of generative AI’s potential impacts and how—or even whether—to respond. Fundamental questions remain unanswered: How do we ensure workers can proactively shape generative AI’s design and deployment? What will it take to make sure workers benefit meaningfully from its gains? And what guardrails are needed for workers to avoid harms as much as possible? 

These animating questions are the heart of this report and a new multiyear effort we have launched at Brookings with a wide range of external collaborators. Through research, worker-centered storytelling, and cross-sector convenings, we aim to enhance public understanding, inform policymakers and employers, and shape our societal response toward a future where workers benefit meaningfully from AI’s gains and, as much as possible, avoid its harms. 

In this report, we frame generative AI’s stakes for work and workers and outline our concerns about the ways we are, collectively, underprepared to meet this moment. Next, we provide insights on the technology and its potential impact on jobs, drawing on our analysis of detailed data from OpenAI (described here) that explores task-level exposure for over a thousand occupations in the labor market. Finally, we discuss three priority areas for a proactive response—employer practices, worker voice and influence, and public policy levers—and highlight immediate opportunities as well as gaps that need to be addressed. Throughout the report, we draw on insights from a recent Brookings workshop we convened with more than 30 experts from different disciplines—policy, business innovation and investment, labor, academic and think tank research, civil society, and philanthropy—to grapple with those fundamental questions about AI, work, and workers. 

The scope of this report is more limited than the full suite of concerns about AI’s impact on workers. Conscious that our effort builds on an already robust body of academic work, dedicated expertise, and policy momentum on key aspects of job quality and harms from AI (including privacy, surveillance, algorithmic management, ethics, and bias), our primary focus is addressing some of generative AI’s emerging risks for which society’s response is far less developed, especially risks to livelihoods. 

[govindhtech]

Gemini Code Assist Enterprise: AI App Development Tool

Introducing Gemini Code Assist Enterprise’s AI-powered app development tool that allows for code customisation.

The modern economy is driven by software development. Unfortunately, due to a lack of skilled developers, a growing number of integrations, vendors, and abstraction levels, developing effective apps across the tech stack is difficult.

To expedite application delivery and stay competitive, IT leaders must provide their teams with AI-powered solutions that assist developers in navigating complexity.

Google Cloud thinks that offering an AI-powered application development solution that works across the tech stack, along with enterprise-grade security guarantees, better contextual suggestions, and cloud integrations that let developers work more quickly and versatile with a wider range of services, is the best way to address development challenges.

Google Cloud is presenting Gemini Code Assist Enterprise, the next generation of application development capabilities.

Beyond AI-powered coding aid in the IDE, Gemini Code Assist Enterprise goes. This is application development support at the corporate level. Gemini’s huge token context window supports deep local codebase awareness. You can use a wide context window to consider the details of your local codebase and ongoing development session, allowing you to generate or transform code that is better appropriate for your application.

With code customization, Code Assist Enterprise not only comprehends your local codebase but also provides code recommendations based on internal libraries and best practices within your company. As a result, Code Assist can produce personalized code recommendations that are more precise and pertinent to your company. In addition to finishing difficult activities like updating the Java version across a whole repository, developers can remain in the flow state for longer and provide more insights directly to their IDEs. Because of this, developers can concentrate on coming up with original solutions to problems, which increases job satisfaction and gives them a competitive advantage. You can also come to market more quickly.

GitLab.com and GitHub.com repos can be indexed by Gemini Code Assist Enterprise code customisation; support for self-hosted, on-premise repos and other source control systems will be added in early 2025.

Yet IDEs are not the only tool used to construct apps. It integrates coding support into all of Google Cloud’s services to help specialist coders become more adaptable builders. The time required to transition to new technologies is significantly decreased by a code assistant, which also integrates the subtleties of an organization’s coding standards into its recommendations. Therefore, the faster your builders can create and deliver applications, the more services it impacts. To meet developers where they are, Code Assist Enterprise provides coding assistance in Firebase, Databases, BigQuery, Colab Enterprise, Apigee, and Application Integration. Furthermore, each Gemini Code Assist Enterprise user can access these products’ features; they are not separate purchases.

Gemini Code Support BigQuery enterprise users can benefit from SQL and Python code support. With the creation of pre-validated, ready-to-run queries (data insights) and a natural language-based interface for data exploration, curation, wrangling, analysis, and visualization (data canvas), they can enhance their data journeys beyond editor-based code assistance and speed up their analytics workflows.

Furthermore, Code Assist Enterprise does not use the proprietary data from your firm to train the Gemini model, since security and privacy are of utmost importance to any business. Source code that is kept separate from each customer’s organization and kept for usage in code customization is kept in a Google Cloud-managed project. Clients are in complete control of which source repositories to utilize for customization, and they can delete all data at any moment.

Your company and data are safeguarded by Google Cloud’s dedication to enterprise preparedness, data governance, and security. This is demonstrated by projects like software supply chain security, Mandiant research, and purpose-built infrastructure, as well as by generative AI indemnification.

Google Cloud provides you with the greatest tools for AI coding support so that your engineers may work happily and effectively. The market is also paying attention. Because of its ability to execute and completeness of vision, Google Cloud has been ranked as a Leader in the Gartner Magic Quadrant for AI Code Assistants for 2024.

Gemini Code Assist Enterprise Costs

In general, Gemini Code Assist Enterprise costs $45 per month per user; however, a one-year membership that ends on March 31, 2025, will only cost $19 per month per user.

Read more on Govindhtech.com

[industrynewsupdates]

A Comprehensive Overview of Generative AI In Coding Market Landscape

The global generative AI in coding market size is expected to reach USD 106.3 million by 2030, according to a new report by Grand View Research, Inc. The market is anticipated to expand at a CAGR of 25.2% from 2023 to 2030. Generative AI's impact on coding rapidly expands as developers use advanced models and successors to streamline software development. These models generate code snippets, offer creative solutions, automate documentation, enhance code comprehension, and enable rapid prototyping. As the technology evolves, its ability to address diverse programming languages and specific domains grows, empowering developers with efficient coding assistance and accelerating the iterative development process.

The rise in the development of AI models specifically designed for code generation propels the market forward. These models might be fine-tuned on programming languages, frameworks, and software development contexts, making their suggestions even more relevant and accurate. For instance, GitHub Copilot is an AI-driven coding tool that GitHub, OpenAI, and Microsoft Corporation developed. This tool offers code suggestions in Visual Studio, Neovim, and JetBrains development environments. Its ability to suggest relevant code snippets and auto-completion can save time and effort while improving code quality and consistency.

By integrating generative AI and low-code, systems can autonomously manage tasks, reducing human involvement. Low-code software democratizes development within organizations, while generative AI enhances efficiency. This synergy could streamline app creation in low-code and no-code platforms, where AI generates code from visual input. According to Microsoft's Low-Code Signals 2023 report, 87% of innovation leaders and IT professionals anticipate improved utilization through increased AI and automation within low-code platforms.

Gather more insights about the market drivers, restrains and growth of the Generative AI In Coding Market

Generative AI In Coding Market Report Highlights

• Code Generation segment dominated the market with a revenue share of 37.4% in 2022. As software development becomes more pervasive across industries, the demand for code is increasing. Generative AI assists in meeting this demand by accelerating code production.

• The North America region dominated the market with a revenue share of 29.3% in 2022. The interconnected tech ecosystem in North America encourages cross-industry collaboration and knowledge-sharing, further fueling the adoption of generative AI in coding.

• The collaboration among AI research, hardware progress, and vast datasets drives market by furnishing developers with more potent and streamlined tools. These tools simplify coding tasks, resulting in enhanced efficiency and the creation of superior software products.

• As artificial intelligence gains more recognition for its effectiveness across industries, there's a rising interest in utilizing generative AI for coding, driven by its potential to enhance coding processes. This interest stems from understanding AI's value in improving coding efficiency.

Generative AI In Coding Market Segmentation

Grand View Research has segmented the global generative AI in coding market based on operation, application, industry vertical and regional.

Generative AI in Coding Operation Outlook (Revenue, USD Million; 2018 - 2030)

• Code Generation

• Code Enhancement

• Language Translation

• Code Reviews

Generative AI in Coding Application Outlook (Revenue, USD Million; 2018 - 2030)

• Data Science and Analytics

• Game Development and Design

• Web and Application Development

• IoT and Smart Devices

Generative AI in Coding Industry Vertical Outlook (Revenue, USD Million; 2018 - 2030)

• BFSI

• Media and Entertainment

• IT & Telecom

• Healthcare and Life Sciences

• Transport & Logistics

• Retail & E-commerce

Generative AI in Coding Regional Outlook (Revenue, USD Million; 2018 - 2030)

• North America

o U.S.

o Canada

• Europe

o U.K.

o Germany

o France

• Asia Pacific

o China

o Japan

o India

o South Korea

o Australia

• Latin America

o Brazil

o Mexico

• Middle East and Africa

o KSA

o UAE

o South Africa

Order a free sample PDF of the Generative AI In Coding Market Intelligence Study, published by Grand View Research.

[blogchaindeveloper]

10 Ways ChatGPT Can Improve Your Productivity

An innovative artificial intelligence application called ChatGPT was created to increase workplace productivity. It can revolutionize various activities and obstacles thanks to its vast training in diversified information and human-like communication abilities.

You may automate monotonous processes with ChatGPT, saving you time and alleviating tension. Its context comprehension allows it to produce intelligent responses that seem natural, simplifying communication and improving data analysis and decision-making procedures. It can expedite project management, enhance customer service, personalize training and development, and encourage innovation and brainstorming sessions. ChatGPT is helpful for coding, content creation, document creation, and editing. It is an essential tool for streamlining processes and increasing general productivity because of its flexibility and adaptability.

To get the most out of ChatGPT, broaden your knowledge and experience in conversational agents and chatbots. You can become more knowledgeable and adept with ChatGPT by gaining knowledge in ChatGPT certification, chatbot training, certified chatbot expert status, AI chatbot competence, or chatbot engineer abilities. It may present fresh chances for you to perform more productively.

Given the increasing prevalence of chatbots and conversational agents in various businesses and areas, these abilities are highly valued in today's labor market. Using ChatGPT to its full potential and gaining these applicable credentials will help you become more productive at work. Your efficiency and knowledge can also make an impression on clients and coworkers.

This post will go over ten ways ChatGPT can significantly increase your productivity, regardless of your job: data analyst, creative marketer, or busy executive. You'll be able to demonstrate your efficacy and proficiency while achieving more in less time by putting these recommendations into practice.

1.Automate Routine Operations

The load of tedious, repeated duties that take up significant time and energy is among the most common obstacles to productivity. These duties include answering often-asked inquiries, scheduling meetings, filling out paperwork, keeping track of documents, and reminding people to do things.

Thankfully, ChatGPT provides an answer by making it possible to automate these kinds of jobs by building intelligent chatbots. Chatbots are computer programs that converse with users by text or voice, providing help information or taking actions in response to input from the user.

You can easily create chatbots with ChatGPT for various platforms and uses. For example, you can make a chatbot to respond to customer inquiries on your website or social media pages. You may build a chatbot that can effectively set up email or calendar appointments. You can set up a chatbot to automatically fill out forms or update data in your ERP or CRM system.

2. Simplify Interaction

An essential component of any successful business is effective communication. Conversely, it can cause confusion and distraction if not managed appropriately. Coordinating many lines of communication—like emails, phone conversations, instant messages, and video chats—can be difficult while corresponding with different people, including partners, suppliers, clients, and coworkers.

Various useful communication tools are available from ChatGPT to help you be more productive and efficient. It may condense multiple documents, including emails, reports, meeting notes, and articles, highlighting essential ideas and takeaways for simple reading. You can trust ChatGPT to write emails according to your templates or prompts, ensuring correct language, spelling, tone, and clarity. ChatGPT can quickly translate written materials into other languages, transcribe audio or video files, and more. It can also convert speech to text or generate speech based on input. Additionally, ChatGPT can assist you in creating expert presentations using data or outlines, and it can even improve them with animations and voice-overs. ChatGPT revolutionizes your conversation experience with these clever features.

 3. Improve Your Ability to Analyze and Make Decisions

Since data is the lifeblood of any organization, businesses must analyze their data and make decisions based on it. However, this work can become challenging when dealing with large amounts of data from many sources and formats. Complex issues frequently develop that necessitate considering several variables and standards.

ChatGPT makes it simple to ask questions about data and get responses in plain English, facilitating conversation. It also helps with data visualization by creating aesthetically pleasing tables, charts, graphs, and maps using your supply data. Regarding data analysis, ChatGPT is excellent at finding patterns, trends, outliers, correlations, or anomalies. This allows it to provide insightful analysis and recommendations. With ChatGPT, you can compare data according to many criteria, which makes it easier to evaluate possibilities and create well-informed lists of pros and disadvantages. ChatGPT's predictive features enable it to develop and test hypotheses and predict outcomes and scenarios based on your data.

4. Customize Education and Training

Any organization that wants to increase its performance, productivity, knowledge, and skills must prioritize training and development. However, if these procedures are carried out correctly, their efficacy may be protected, leading to expensive and time-consuming outcomes. The problem of coping with cliched or out-of-date courses, resources, or approaches that might not suit each student's interests or preferences must be addressed.

Bright, individualized learning solutions are available from ChatGPT and cater to your unique requirements. It offers progress tracking and insightful feedback in addition to helping create personalized learning paths that align with your objectives, interests, abilities, and competence level. Interactive tests, quizzes, exercises, and assignments tailored to your learning goals and subject matter can be created with ChatGPT. It goes one step further by verifying your responses and providing thorough justifications. 

ChatGPT generates summaries, notes, flashcards, or cheat sheets based on your learning materials or sources to help you retain the information you've learned. It can even produce mnemonics, acronyms, or analogies to improve memory retention. Additionally, ChatGPT facilitates comprehension and application by creating scenarios, stories, case studies, and examples. It also provides challenging questions or tasks to evaluate your understanding and practical abilities.

5. Boost Client Support

Any firm must be able to draw in, keep, and please consumers while building its brand and income. It draws attention to how vital customer service is. Providing excellent customer service may be easy, but if not done correctly, it is manageable. Handling consumer requests, complaints, and comments across multiple channels and platforms can take a lot of work. It's frequently essential to handle delicate or complicated circumstances that demand tact and sensitivity.

ChatGPT provides witty and approachable customer service solutions. It makes it possible to develop chatbots that can effectively handle customer requests, complaints, and comments via various platforms and channels. Customers can receive customized information, advice, recommendations, or solutions from these chatbots according to their needs and preferences. Additionally, ChatGPT improves customer relations by producing replies that correspond with users' messages or emotions. It also guarantees that accuracy, clarity, tone, and politeness are maintained. Creating scripts or templates for various scenarios or situations and providing advice and best practices for efficient communication make customer service discussions more seamless.

ChatGPT enables companies to obtain insightful data by creating surveys or reviews based on their customers' experiences or input. Creating incentives or awards based on loyalty or general contentment even helps promote customer involvement and satisfaction.

6. Simplify the Management of Projects

Any firm must successfully plan, carry out, oversee, manage, and close down projects, emphasizing project management's significance. Project management mistakes can result in excessive demands and complexity. Managing various activities, resources, stakeholders, risks, problems, adjustments, and deadlines is frequently necessary.

Project management becomes streamlined effortlessly because of ChatGPT's sophisticated features. Creating project plans based on your goals, scope, budget, timetable, and quality streamlines the procedure and guarantees a thorough and well-organized method. It makes effective progress tracking possible by giving reports and real-time updates on the project's state. Task and role delegation is streamlined thanks to ChatGPT, which helps allocate team members according to their availability and skill sets. 

It also keeps track of each member's performance and provides insightful feedback. Because ChatGPT facilitates accessible communication with team members and stakeholders across several channels and platforms, effective communication is also improved. It makes meetings and conversations run more smoothly while capturing minutes and action items for comprehensive documentation. 

The risk and problem management features of ChatGPT enable the early detection and effective remediation of possible project roadblocks. It also helps with conflict resolution and change implementation that may come up during the project.

7. Boost Originality and Idea Generation

Any business must be able to come up with new ideas, solve problems, innovate, and improve its offerings, which emphasizes the value of creativity and brainstorming. Nevertheless, difficulties and annoyances may arise from these methods' poor use. Successful creativity and brainstorming sessions require addressing typical challenges, including breaking through mental hurdles, finding inspiration, and avoiding groupthink.

ChatGPT offers clever and entertaining ways to spark your imagination, which can help you improve creativity and brainstorming. It is excellent at producing ideas in response to your prompts or keywords, assisting you in exploring novel avenues, or honing already-existing notions. Producing striking illustrations, scenarios, case studies, or narratives sparked by your thoughts or concepts facilitates the creative process. To evaluate the viability and potential of your ideas, it might also produce challenging or thought-provoking questions. ChatGPT inspires creativity by creating catchy headlines, slogans, names, titles, or logos that complement your ideas. Moreover, ChatGPT can produce code for you based on your conceptions or ideas.

8. Boost the Creation and Editing of Documents

Any organization must be able to communicate messages, information, or data effectively and professionally, which highlights the significance of creating and updating documents. These chores must be carried out correctly to avoid becoming tiresome and time-consuming. Successful document development and editing processes often require addressing formatting issues, fixing grammatical and spelling faults, and preventing plagiarism.

By giving you clever and straightforward ways to generate and edit documents, ChatGPT can help you enhance document creation and editing. It is excellent at creating documents using templates or prompts, providing an easy place to start when developing material. It acts as a competent editor, quickly adding your comments or recommendations to improve your writing.

Verifying grammar, spelling, punctuation, tone, clarity, and accuracy guarantees the caliber of your work. Furthermore, ChatGPT recommends enhancements or modifications to polish your texts further. By giving you document summaries specific to your needs or target audience, it also helps to condense material. ChatGPT can rewrite or paraphrase your texts to conform to your desired style and tone. It helps with precise source citation generation according to your chosen format or style and helps with proper citation formatting. ChatGPT can examine your documents for plagiarism, guaranteeing their uniqueness and integrity.

9. Produce Code and Content

Any organization needs to create value, engage customers, foster trust, and spur growth; these are just a few reasons that content and code are essential. However, creating content and code can be demanding and complex if done incorrectly. Significant hurdles that must be overcome to create text and code successfully include writer's block, gaining sufficient information, and fixing coding errors.

ChatGPT can assist you in producing code and content by giving you quick and easy methods. It helps you quickly generate optimized SEO, readability, or engagement content while adhering to your preferred topic, keyword, or structure. ChatGPT does best by customizing code snippets to your favorite language, framework, or function. It can also help with debugging and rewriting already-written code. Producing code and content based on your input or data ensures smooth integration and increases productivity. It also makes data or input to support your code or content.

10. Enhance Your Process

Increasing productivity, increasing efficiency, and streamlining procedures are critical for any firm, which emphasizes the significance of workflow optimization. However, workflow optimization can be difficult and time-consuming if done incorrectly. Successful process optimization requires addressing common obstacles such as bottlenecks, delays, errors, and waste.

By giving you clever and easy methods to handle your work, ChatGPT can help you maximize your workflow. It helps create workflows specific to your objectives, assignments, and resource availability. Additionally, ChatGPT facilitates workflow automation by creating automated procedures triggered by the rules or triggers you designate. It helps with task identification and organization according to impact, priority, or urgency. It also makes delegating easier by recommending team members who are qualified and available for particular tasks.

ChatGPT also makes tracking work based on predefined metrics or indicators easy, facilitating progress monitoring. It facilitates assessing work about predetermined benchmarks or standards. ChatGPT provides insightful analysis and recommendations to enhance the quality of your work by utilizing your feedback and suggestions. To improve performance in the future, it also makes continuous learning easier by evaluating results and outcomes.

Utilize ChatGPT More Effectively and Efficiently by Acquiring New Certifications and Skills

ChatGPT is a highly adaptable tool with great potential to increase efficiency at work. Nevertheless, it can be helpful to obtain extra knowledge and certifications about chatbots and conversational agents to utilize their potential and optimize productivity fully.

Competence in chatGPT certification, chatbot engineering, certified chatbot knowledge, chatbot training, and AI chatbot knowledge are highly valued in today's industry. These abilities are in great demand due to chatbots' growing popularity and usefulness across a wide range of companies and domains.

There are lots of internet tools accessible to help you get these certifications and abilities. These resources include books, blogs, podcasts, videos, guides, tutorials, and courses, among many other types of content. You can customize your learning experience by selecting what best suits your needs and interests by considering cost, time, format, and degree of difficulty.

Through the utilization of these materials, you can increase your comprehension and usefulness of ChatGPT. Adding these qualifications and abilities to your professional toolkit can help you make better use of ChatGPT and increase productivity in your work.

In summary

With ChatGPT, a practical artificial intelligence technology, you may significantly increase your efficiency at work. It can help you improve customer service, automate repetitive tasks, improve document creation and editing, generate content and code, improve communication, improve data analysis and decision-making, personalize training and development, and streamline project management.

Additionally, ChatGPT can assist you in using it more successfully and efficiently by teaching you new competencies and credentials connected to conversational agents and chatbots. As an illustration, you can join the Blockchain Council, a reputable association of professionals and enthusiasts dedicated to promoting Blockchain Knowledge, Products, Use Cases, Research, and Development for a Better World. You can learn ChatGPT certification, chatbot training, certified chatbot expert status, AI chatbot expertise, and chatbot engineering abilities by enrolling in one of the many online courses and certifications offered by Blockchain Council.

Given the increasing popularity and use of chatbots and conversational agents across various sectors and disciplines that utilize blockchain technology, these are some of the most valuable and in-demand skills available today.

By acquiring these competencies and certifications from the Blockchain Council, you may improve your comprehension and use of ChatGPT. By utilizing ChatGPT for various tasks and blockchain-related projects, you can also increase your output at work.

[rx-review]

SEOBuddy AI Review - Boost Your Website Google's First Page

Introduction of SEOBuddy AI Review

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SEOBuddy AI Review - Overview

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SEOBuddy AI Review - Key Features

Develop & power up your dream sites live by using the next-gen ChatGPT-4o AI.

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Pros & Cons of SEOBuddy AI Review

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SEOBuddy AI Review - FAQs

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[jeffhirsch]

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Rally Respite After Big Best Six Months Gains

Monday is the beginning of the last month of the ��Best Six Months (BSM)” (November-April) for the Dow and S&P 500 – and what a banner one it’s been so far. From our Seasonal MACD Buy Signal on October 9, 2023, through the close on March 28, 2024, DJIA is up 18.46% and S&P 500 is up 21.19% – more than double the historical average BSM gains. Our Best Six Months Seasonal MACD Sell Signal can trigger anytime on or after the first trading day of April, which is Monday April 1st this year. NASDAQ’s Best 8 Months end in June, which is up 21.47% since our buy signal, not quite double the average but give it time.

The big rewards we have reaped this Best Six Months and year-to-date so far have not left much on the table until later this year. Risks are more elevated now. Sentiment continues to run high. Valuations are extended. Geopolitical tensions have not eased. And persistent inflation pressures have the Fed in no rush to cut rates. As the election campaign rhetoric heats up and the Best Six Months comes to a close be prepared to shift to a more cautious stance when we issue our Best Six Months Seasonal MACD Sell Signal. We do not expect a bear market or major correction. We do not Sell in May and go away. We sell some things, tighten stops and consider defensive positions if warranted.

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[aftokrator-official]

The breast cancer detection research is legitimately very cool, but the third screenshot is incredibly misinformed about what AI is and how it works, to a degree that I think is actively harmful. I'll take it line by line.

"Analytical ai vs generative ai": these are not actually meaningful or distinct categories. They are use cases. "AI" is essentially a shorthand for a set of techniques that computer scientists call "deep learning" - basically, running certain kinds of calculations on large data sets to create statistical models that can, we hope, make predictions about similar data. This is still a pretty broad field, and there's a lot of different techniques and ways they can be applied - you probably can't just take ChatGPT's model and retrain it to identify breast cancer (and even if you could, you definitely shouldn't). But ALL deep learning is based on the same principles and the same kinds of calculations. It's a bit like the difference between two different 3D game engines - say, Unity and Unreal Engine. There are distinctions between them, sure. But both of them ultimately solve the same problems: that is, rendering objects in a 3D space and simulating physics in realtime. The basic concepts are the same, and they use the same hardware to get there.

"one of these is doing cataloguing and diagnoses and a whole bunch of stuff that's super useful": No! No no no! I'm not saying there aren't very cool, useful ways to use AI for data analysis, but there's nothing inherently good about "analytical" AI. For example, police departments using it for "predictive policing" (effectively just technologically assisted profiling), or facial recognition (which is known to be less accurate for people of color!), or government surveillance, or insurance companies rejecting claims based on AI analysis.

Even in cases that aren't as clear-cut and harmful as these, you have to be really careful. The breast cancer detection system from the original post is legitimately amazing, and has the potential to save so many lives! But it would still be profoundly irresponsible to rely solely on this technology for diagnosis. Remember, AI/deep learning is ultimately just applied statistics. There will always be outliers, false positives and false negatives, and unexpected real-world scenarios that the AI model's training data did not account for. This technology is a tool that has the potential to improve medical experts' ability to make early cancer diagnoses. It is not, itself, a medical expert. And while I don't think anyone reading this post will disagree with that, it's very easy to imagine organizations cutting costs by over-reliance on technology like this, while cutting human experts out of the process. And in the context of cancer detection and treatment, that would absolutely cost people their lives.

"The other is... being sold everywhere as solving problems but insofar as I'm concerned it mostly hallucinates language": Yeah, I do pretty much agree with this! Aside from the false dichotomy of "generative"/"analytical" AI, it IS true that AI is currently an overhyped marketing buzzword, and in that marketing hype context it usually means LLMs (large language models), such as ChatGPT. Investors and venture capitalists are fucking obsessed with this stuff, cramming it into use cases that don't really work and don't really make sense, and driving the rest of us crazy (even me, someone who works in tech and is generally interested in deep learning).

Do I think LLMs are inherently bad and useless? No, not really. There are a number of LLMs designed to write code, for example; these aren't a substitute for knowing how to code, yourself (you must know how to catch mistakes they will inevitably make) but some people do find them useful as a sort of smarter autocomplete, speeding up the more tedious and repetitive parts of writing code. Not revolutionary, rather unremarkable really, but genuinely helpful for devs who choose to use them responsibly. A far cry from AI-generated search results, or a chatbot inexplicably crowbarred into one's weather forecast app, or any of the other bullshit "features" are the hot new gimmick of the week. Nobody asked, nobody wants them, and they don't even work as advertised because they are being used for things LLMs can't fucking do, so please stop making them, we are all begging you.

"Analytical AI is also less resource intensive because it trains its model and that's it": This is COMPLETELY incorrect and makes absolutely no sense. There is no such thing as an "AI" that trains its model and then does nothing else ever. What would even be the point? Remember, an "AI" is just a VERY large and complex statistical prediction model. The larger and more complex, the more resources it will take for a computer to run those calculations and make the predictions it's been trained to make. That's true whether the prediction is "does this tissue sample show early signs of breast cancer?" or "what text should come next after this prompt?" Even if the output is very "simple," it'll still take a lot of computation power to produce that result if the statistical model is large and complex.

I'm not an expert about energy costs, but there are a lot of wild, overblown claims going around about AI energy use that aren't particularly well sourced. A lot of people seem to have the perception that AI uses energy in similar quantities (and with similar wastefulness) as NFTs/crypto, which isn't really true. Other people who are better informed than me have talked about this in more detail! For now, I'll just say that training AI models will always be more resource-intensive than using them, and there are definitely conversations to be had about best practices there... I, personally, am most critical of companies with enormous proprietary models who are not especially transparent about how they are trained or how much they cost to run. It's better for everyone - for the environment AND for science - if we can share this stuff and learn from one another rather than reinventing the wheel each time, at great expense.

No matter what your feelings are on "AI", I encourage everyone to learn a little about how deep learning/machine learning works - there are so many misconceptions flying around in the discourse, and it's not helpful to anyone. It's not some earth-shattering innovation that'll magically make everyone's lives better, and it's not some monstrous threat either - it's just a kind of technology, and it's humans who decide to use it in helpful or harmful ways - or, most realistically, a mixture of both.

[kajalbasolanki]

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