#deepseek ai bot

[coingabbarnew]

Crypto Market Crash: 850 Million Dollars Wiped Out

The crypto market has experienced a massive crash, with 850 million dollars being wiped out in a short span. This drastic loss has been triggered by a combination of factors including market correction, regulatory concerns, and investor panic. The downturn has affected a wide range of digital assets, with many cryptocurrencies seeing sharp declines. Traders and investors are left questioning the stability of the market, while others are looking for potential buying opportunities as prices hit new lows. Stay updated for further analysis! To know more- crypto market

[sawbeentheblog]

Baidu's Ernie Bot Goes Free As AI Battle Intensifies Against DeepSeek, OpenAI

Chinese search engine giant Baidu announced on Thursday that its AI chatbot, Ernie Bot, will be available for free for users starting April 1 on both desktop and mobile devices on improved technology and reduced costs to regain momentum in AI space. The move comes as competition in AI market is heating up, mainly from China’s own DeepSeek which offers free AI chatbot services at lower…

[fraoula1]

The Future of Customer Service with Chatbot Builder

In today's fast-paced digital world, customer service is rapidly transforming. Thanks to advancements in artificial intelligence and automation, businesses are finding innovative ways to improve user experiences. Chatbot builders are leading this charge, becoming essential tools for organizations looking to enhance their customer interactions. With the ability to mimic conversation and deliver instant support, chatbots are reshaping customer service across different sectors.

Understanding Chatbot Builders

Chatbot builders are user-friendly platforms that allow anyone to create and launch chatbots without needing extensive coding skills. Equipped with intuitive interfaces, these tools let businesses customize their chatbots to meet specific customer needs. The rise of chatbot technology can be linked to its ability to reduce costs, provide 24/7 support, and manage a large number of inquiries at once.

For example, companies that implement chatbots can automate responses to frequently asked questions (FAQs), leading to efficiency gains. Statistics show that businesses using chatbots can handle up to 80% of routine inquiries, allowing human teams to focus on more complex tasks.

Enhancing Customer Experience

Providing timely and relevant answers is the heart of effective customer service. Chatbots excel here, quickly addressing frequent inquiries, offering product suggestions, and even assisting with bookings and purchases. This level of support improves the overall customer experience and lightens the workload for human agents.

For instance, a leading e-commerce site implemented a chatbot that reduced response times by over 40%. The bot could manage routine interactions, allowing customer service reps to devote their time to complex issues, which boosted employee satisfaction rates by 20%.

Additionally, chatbots can gather user data and analyze interactions, leading to ongoing enhancements in response quality. This capability allows businesses to adapt their customer service strategies based on real-time feedback, creating a more tailored experience for users.

Cost-Effectiveness and Efficiency

Adopting a chatbot can drastically lower operational costs. Businesses that automate common inquiries can redirect their human resources to tackle more intricate and sensitive customer issues. This not only enhances efficiency but also allows employees to engage in tasks that add significant value to the organization.

Moreover, chatbots have no limitations when it comes to working hours. They can provide support 24 hours a day, 7 days a week, ensuring customers receive timely assistance. A survey revealed that customer satisfaction rates increased by 30% when businesses adopted a chatbot for immediate responses.

Scalability and Flexibility

As businesses grow, the influx of customer inquiries does too. Chatbot builders provide scalable solutions that can adapt to evolving needs. Companies that see spikes in traffic, such as during holiday seasons, can rely on chatbots to handle a significant volume of queries without sacrificing response time or quality.

Additionally, many chatbot platforms integrate effortlessly with existing business tools. This integration allows companies to manage customer interactions through a centralized system, enhancing communication. For example, linking chatbot builders with Customer Relationship Management (CRM) systems can ensure all customer interactions are tracked, leading to better insights and strategies. Studies indicate that businesses with integrated systems see a 25% increase in operational productivity.

Leveraging AI and Machine Learning

Unlike traditional chatbot systems that follow fixed scripts, modern chatbot builders harness artificial intelligence (AI) and machine learning. This technology enables chatbots to learn from interactions, continuously improving their responses. With natural language processing capabilities, these chatbots can pick up context and sentiment, making conversations feel more engaging and human-like.

The expansion of chatbot capabilities also means they can tackle more complex tasks. It's no longer just about answering basic questions; chatbots can offer product recommendations, troubleshoot issues, and facilitate simple transactions. This evolution has opened new pathways for businesses to boost customer engagement. Reports suggest that companies using AI-enhanced chatbots see a 20% increase in customer retention rates.

Challenges and Considerations

Despite the clear advantages, businesses face challenges in effectively implementing chatbot builders. One critical concern is ensuring that the chatbot reflects the company's brand voice and provides consistent experiences at all customer touchpoints. While chatbots are great at handling numerous queries, some situations still need human touch.

To overcome these hurdles, companies should equip their chatbots with clear pathways to escalate issues to live agents when necessary. This setup guarantees customers receive the support they need when the bot can't resolve their issue. Regular updates to the chatbot's knowledge base are essential to keep it relevant and accurate.

The Path Forward

The evolution of customer service is closely linked to the rise of chatbot technology. With the support of chatbot builders, businesses can create efficient, scalable, and cost-effective support systems that cater to their customers' needs. As these bots become more advanced, their influence on customer service will only strengthen.

For companies aiming to improve their customer service strategies, embracing chatbot builders can be transformative. They deliver instant responses while freeing up human resources for more complex tasks. With customer expectations on the rise, integrating chatbot technology will be vital for achieving outstanding satisfaction and loyalty.

Adopting this technological shift is about more than just keeping pace. It’s an opportunity to lead in an increasingly competitive market. Taking the first step into chatbot technology today could lay the groundwork for exceptional customer service in the future.

[jcmarchi]

DeepSeek’s R1: A Useful Reminder

New Post has been published on https://thedigitalinsider.com/deepseeks-r1-a-useful-reminder/

DeepSeek’s R1: A Useful Reminder

As a college educator and former IT industry veteran, I find that the hype around China’s DeepSeek R1 model is a useful reminder of three things.

The first is that generative AI is no longer just about processing vast amounts of content to generate relevant responses to prompts; it’s also about cognitive reasoning (the “R” in R1).

The promise of reasoning large language models (LLM’s) is that massive knowledge retrieval and cognitive processing capabilities – once the exclusive realm of brainiacs with supercomputers – is now in the hands of nearly everyone. Thanks to a new generation of advances in efficiency-boosting techniques, there are models small enough to run on a conventional laptop that can support multiple intelligent agents that can autonomously perform complex, interactive tasks.

Secondly, the generative AI revolution is foremost about innovation and creativity – it’s not just an arms race for the most powerful hardware, size of training data sets, or number of model parameters. Successful adoption of these technologies will not be determined by the Big Tech firms with massive, energy-gobbling super computers training multi-billion dollar models – but by countries and organizations that invest in human capital to prepare them for this new wave.

Thirdly, and building off that last point, America doesn’t seem all that well positioned for the dramatic changes coming to our economy and society. I’ll cite two examples: high education and corporate America.

Higher-Ed

In most institutions of higher learning, an undergraduate’s first big decision is to decide whether to pursue a Bachelor of Arts (BA) degree, which is associated with a broader, more interdisciplinary education, or a Bachelor of Science (BS) degree, which is more focused on developing skills and hands-on experience in specific fields.

In the age of AI, this is a hopelessly outdated dichotomy, as both sets of disciplines are becoming essential in the workplace.

Fact is, most first-year students don’t have anywhere near the knowledge or insight of what it’s like to work in different types of jobs, or even the relative strengths and weaknesses of their own abilities, talents, skills and aptitudes. And yet, most first-years are required to declare a major, which will be an easy decision for only that small percent who (for better or worse) know (or at least think they know) what field they want to pursue: engineering, science, medicine, law, etc.

We need a much different, career-ready, broader, interdisciplinary approach to higher education that acknowledges that a college graduate’s first full-time job may have nothing to do with the degree they earned or their major; that their college experience will represent merely the first stage in life-long journey of continuous learning – upskilling, credentialing, reinvention, career-switching – for roles we can’t even imagine now.

Also, as educators, we need to develop new strategies to handle AI plagiarism and navigate the dangers of chat bots becoming intellectual shortcuts, or “cognitive offloading” – the tendency to rely on external tools rather than developing internal capabilities.

In an age when knowledge is separated from understanding, there’s just too much temptation to simply prompt AI for an immediate answer or solution instead of wrestling to understand a concept or solve a problem.

Corporate IT

Most corporations also don’t seem to realize the organizational implications of these new technologies.

Current IT roles and structures reflect the organizational requirements from the previous, digital revolution. Those functions arose from the specialized expertise required for humans to use and interact with computers – programming, data engineering, computer architecture, network administration, information security, etc.

In contrast, generative AI (and the whole field of Natural Language Processing that preceded it) is about designing and training computers to interact with humans.

As a result, rank and file employees are inventing brilliant (and sometimes dangerous) ways to use these technologies. Organizations are struggling to come up with workable policies, procedures and controls to maximize the potential productivity benefits while minimizing the risks.

A key problem is that in most corporations, data science expertise tends to be concentrated in IT departments, most of which still operate as secret guilds with their own mysterious language and practices that are organizationally and functionally isolated from core business units. I believe that the coming Productivity Revolution calls for new types of organizational roles and structures, in which data expertise is not sequestered in a specialized function but interconnected with almost every aspect of the operation.

And there’s also the data challenge. In most organizations, adopting AI is about customizing LLM’s to execute specialized use cases using proprietary data. While users of the data in the lines of business want completely accurate, clean and well-managed data, the individual owners of the data in IT don’t have the budget, financial incentive or organizational authority to ensure this level of quality and transparency.

As a result, internal data sets are not discoverable/managed well across the enterprise. Typically different types of data are stored in different places. In response to business user requests, IT provides different views of the data, make different copies (and copies of copies) of the data, and create exposures and abstractions of the data for various different reasons…At this point, no one knows which versions are stale, incomplete, duplicative, inaccurate or their context.

Conclusion

​Generative AI has the potential to transform all forms of knowledge work. At its core, this technology is about the democratization of expertise (for good and bad) – disintermediating specialists such as coders, videographers, illustrators, writers, editors, and just about any type of knowledge worker or “expert.” Never before have humans dealt with a technology that rivaled their own cognitive processing and reasoning abilities – merely their physical strength, endurance, precision of dexterity, and ability to munge and process vast volumes of data.

This exciting new productivity revolution requires new skill sets, capabilities, and organizational structures, in which data expertise is integral to almost every type of business process.

The irony is that as machines achieve greater analytic powers, the status and value of an employee in an organizational hierarchy may become less a function of specialized expertise, experience and credentials, and more of their creative, multi-disciplinary and inter-personal skills.

The time to develop and invest in these capabilities is now.

[ecrivainsolitaire]

A summary of the Chinese AI situation, for the uninitiated.

These are scores on different tests that are designed to see how accurate a Large Language Model is in different areas of knowledge. As you know, OpenAI is partners with Microsoft, so these are the scores for ChatGPT and Copilot. DeepSeek is the Chinese model that got released a week ago. The rest are open source models, which means everyone is free to use them as they please, including the average Tumblr user. You can run them from the servers of the companies that made them for a subscription, or you can download them to install locally on your own computer. However, the computer requirements so far are so high that only a few people currently have the machines at home required to run it.

Yes, this is why AI uses so much electricity. As with any technology, the early models are highly inefficient. Think how a Ford T needed a long chimney to get rid of a ton of black smoke, which was unused petrol. Over the next hundred years combustion engines have become much more efficient, but they still waste a lot of energy, which is why we need to move towards renewable electricity and sustainable battery technology. But that's a topic for another day.

As you can see from the scores, are around the same accuracy. These tests are in constant evolution as well: as soon as they start becoming obsolete, new ones are released to adjust for a more complicated benchmark. The new models are trained using different machine learning techniques, and in theory, the goal is to make them faster and more efficient so they can operate with less power, much like modern cars use way less energy and produce far less pollution than the Ford T.

However, computing power requirements kept scaling up, so you're either tied to the subscription or forced to pay for a latest gen PC, which is why NVIDIA, AMD, Intel and all the other chip companies were investing hard on much more powerful GPUs and NPUs. For now all we need to know about those is that they're expensive, use a lot of electricity, and are required to operate the bots at superhuman speed (literally, all those clickbait posts about how AI was secretly 150 Indian men in a trenchcoat were nonsense).

Because the chip companies have been working hard on making big, bulky, powerful chips with massive fans that are up to the task, their stock value was skyrocketing, and because of that, everyone started to use AI as a marketing trend. See, marketing people are not smart, and they don't understand computers. Furthermore, marketing people think you're stupid, and because of their biased frame of reference, they think you're two snores short of brain-dead. The entire point of their existence is to turn tall tales into capital. So they don't know or care about what AI is or what it's useful for. They just saw Number Go Up for the AI companies and decided "AI is a magic cow we can milk forever". Sometimes it's not even AI, they just use old software and rebrand it, much like convection ovens became air fryers.

Well, now we're up to date. So what did DepSeek release that did a 9/11 on NVIDIA stock prices and popped the AI bubble?

Oh, I would not want to be an OpenAI investor right now either. A token is basically one Unicode character (it's more complicated than that but you can google that on your own time). That cost means you could input the entire works of Stephen King for under a dollar. Yes, including electricity costs. DeepSeek has jumped from a Ford T to a Subaru in terms of pollution and water use.

The issue here is not only input cost, though; all that data needs to be available live, in the RAM; this is why you need powerful, expensive chips in order to-

Holy shit.

I'm not going to detail all the numbers but I'm going to focus on the chip required: an RTX 3090. This is a gaming GPU that came out as the top of the line, the stuff South Korean LoL players buy…

Or they did, in September 2020. We're currently two generations ahead, on the RTX 5090.

What this is telling all those people who just sold their high-end gaming rig to be able to afford a machine that can run the latest ChatGPT locally, is that the person who bought it from them can run something basically just as powerful on their old one.

Which means that all those GPUs and NPUs that are being made, and all those deals Microsoft signed to have control of the AI market, have just lost a lot of their pulling power.

Well, I mean, the ChatGPT subscription is 20 bucks a month, surely the Chinese are charging a fortune for-

Oh. So it's free for everyone and you can use it or modify it however you want, no subscription, no unpayable electric bill, no handing Microsoft all of your private data, you can just run it on a relatively inexpensive PC. You could probably even run it on a phone in a couple years.

Oh, if only China had massive phone manufacturers that have a foot in the market everywhere except the US because the president had a tantrum eight years ago.

So… yeah, China just destabilised the global economy with a torrent file.

[canmom]

can an LLM write a demo?

ongoing LLM probing efforts: I tried giving them a challenge to "write code for a 4k demo to render an ocean scene".

note, in demoscene parlance, a '4k demo' refers to a demo that fits in 4 kilobytes, not one that renders to a 4k monitor. this is a stupidly difficult high-context problem and I didn't expect to really get perfect output. well, shocker, the output was largely not all that impressive in human terms.

Here's the best result I was able to get after a fairly extended dialogue with DeepSeek R1 70b, a 300kb demo using opengl:

many wave, very ocean

I'm kind of wondering why I did this at this point, but I think the main reason was that I started to buy a bit of the hype and wanted to reassure myself that LLMs are still a bit daft?

first I tried two LLMs on lmarena.ai but the site bugged out when I rated them rather than tell me which bots I was talking to.

Both generated what looked like a valid OpenGL program (though I did not attempt to compile either), however, looking closer the output was flawed in various ways. The left one decided to do some limited raytracing in the fragment shader rather than displace a mesh. It claimed to be using Gerstner waves, which would be cool, but a closer look at the output showed it was actually just sines. I'm also not sure quite what it thinks it's doing with the projection - it just seems to take the fragment position as if it were the 3D position.

The second AI does better, generating a plausible-looking vertex and fragment shader file with sine-based vertex displacement. There are some oddities, though, like the fact that it doesn't actually use the generated vertex and fragment shaders as external files, writing them out again as strings in the actual program. Overall, I could believe that if I compiled this it would look like a basic sinusoidal ocean with Phong shading. Old-school but reasonable. Unfortunately I closed the tab so I can't actually test it anymore.

Curious about what might be going on inside these models, I tried asking DeepSeek R1:14b the same challenge. Predictably this smaller model did worse. Its chain of thought prompting gave it a pretty coherent description of how you would write a demo like this, but also revealed some interesting confusions, for example multiple times referring to 'example code' that didn't exist, or quoting things I didn't say ('the user mentioned OpenGL and Vulkan').

When it came to output, though, it only gave me a list of steps to follow and omitted actual code:

There is no 'detailed response provided'.

After issuing some clarifications, DeepSeek R1:14b came up with the idea of creating a text-based demo instead, and generated some plausible-looking code in C++. I figured I might actually compile this, but it used a header file conio.h without explanation. Asking it to clarify led to it figuring out this is an old Windows header, replace it with standard library code, and actually spontaneously add a conditional compilation check for a Windows/Linux difference.

I tried compiling the provided code and ran into some missing libraries. A little coaxing gave a lot of blather to tell me 'you need to #include <cmath>'. A little more coaxing got it to tell me what compiler flags would be needed.

Thus I can present to you Deepseek R1:14b's demo:

Beautiful. Sure to win first place. The 'press q to quit' thing doesn't work. And the compiled binary definitely doesn't fit in 4kb (though it might if I stripped it etc.). But... it tried?

For fairness sake, I'll flood my RAM to try the 70b version as well. To its credit, its 'think' block immediately understands what a '4k demo' is supposed to be. Unfortunately it then goes off the rails and decides to do it in pygame, which is... babe you ain't gonna make a 4k demo in pygame lmao. As the output continued, it forgot that 4k referred to binary size rather than resolution, resolving to test the pygame program which is... not something an LLM can do.

Curiously (and this is something I have noticed a couple of times with DeepSeek), the 'actual' answer after the <think> block basically ignored all that Python stuff and wrote me a basic 'hello triangle' OpenGL program in C. So what was the point of all that thinking? Apparently when it maps from the 'think' LLM path to the 'final output' LLM path, DeepSeek can just... ignore what it was thinking about? The shaders it generated were pretty limited, it basically generates one big triangle over the screen with a scrolling sine wave on it, but I decided to see if it would compile anyway.

I tried asking it for advice on setting up GLFW and GLEW with MinGW and its answer was mostly quite good... but garbled some details (suggesting inconsistent places in where to put the libraries), which luckily I know enough to be able to spot. In the end we get this as the resulting demo:

I've lowered my expectations a lot by this point, but I will give DeepSeek a lot of credit for helping me get a working MinGW/OpenGL build environment. Given that it's a long time since I've fucked about with C/C++, and there's nothing so nice as cargo in this ecosystem, it was a lot faster than figuring it out from the docs.

The executable was more like 400kb than 4kb, so I thought I'd see if I could coax DeepSeek R1-70b to make it smaller. The chain of thought generated here was a genuinely solid discussion of sizecoding techniques, but the real proof would be whether DeepSeek could apply the ideas it pulled out concretely. In the end it gave me a list of ideas to try, including a couple of compiler flags - with this I shaved off 100kb, but it's still far too large.

(Ironically it suggested using "minimalistic frameworks often found in demoscene communities".)

I think I've spent as much time investigating this as I want to. Overall, DeepSeek R1 70b did a pretty good job of understanding what I wanted and generating relevant output, and tbh I could definitely imagine a LLM being useful if I needed to quickly reference info while writing a demo, but evaluated on the original question of 'can this LLM write a 4k demo depicting an ocean scene', the answer is a pretty emphatic no.

Running this on my computer, this took ages to generate the full output token by token - the full interaction ended up taking a couple of hours. But if I did this from scratch, having to look up docs and everything with zero experience with the APIs, I think it would probably take me about the same time to get a working OpenGL program.

Could the 'full size' models do better? Quite probably, but I ain't spending money on this shit.

[toriliashine]

Glad deepseek has fucked shit up, ai companies stealing millions of people's work being called innovation and them CHARGING for the shit they made built on stolen work was pure bullshit. Deepseek itself is p shitty for also being based in stolen work but hey, at least they aren't charging for it ffs . The general shittiness that comes from being an ai bot in the first place

[1256986]

What is DeepSeek OpenAI? A Simple Guide to Understanding This Powerful Tool

Technology is constantly evolving, and one of the most exciting advancements is artificial intelligence (AI). You’ve probably heard of AI tools like ChatGPT, Google’s Bard, or Microsoft’s Copilot. But have you heard of DeepSeek OpenAI? If not, don’t worry! In this blog, we’ll break down what DeepSeek OpenAI is, how it works, and why it’s such a big deal in the world of digital marketing and beyond. Let’s dive in!

What is DeepSeek OpenAI?

The advanced AI platform DeepSeek OpenAI provides businesses and marketers together with individual’s tools to automate operations while enabling better decision-making and improved content generation efficiency. The platform functions as a highly intelligent assistant which analyzes data while generating ideas and creating content and forecasting trends within seconds.

The system's name "DeepSeek" was inspired by its deep information exploration capabilities to generate significant insights. DeepSeek operates through OpenAI's robust technology platform that also powers tools such as ChatGPT. DeepSeek delivers optimized performance for particular circumstances within digital marketing analytics and customer relationship management applications.

Why is DeepSeek OpenAI Important for Digital Marketing?

Digital marketing is all about connecting with your audience in the right way, at the right time. But with so much competition online, it can be challenging to stand out. That’s where DeepSeek OpenAI comes in. Here are some ways it can transform your marketing efforts:

1. Content Creation Made Easy

Your audience engagement depends heavily on producing high-quality content although this process demands significant time investment. Through DeepSeek OpenAI users can instantly create blog posts together with social media captions and email newsletters and ad copy. You gain professional writing support from a team member at no additional expense.

2. Data Analysis and Insights

Marketing is all about data. DeepSeek analyzes website traffic combined with social media performance and customer behavior to generate valuable insights. With its analytics capabilities the system shows you which items customers prefer the most and which promotional strategies generate the highest customer purchases.

3. Personalization at Scale

The demand for personalized customer experiences exists though implementing such solutions manually proves difficult. DeepSeek enables you to produce customized email marketing initiatives together with tailored product recommendation systems and conversational bots that deliver unique messages to every user.

4. Predictive Analytics

DeepSeek's predictive analytics system enables companies to anticipate their business future through forecasting customer behavior and sales performance and industry trends. DeepSeek uses predictive analytics to forecast trends alongside customer behavior and sales performance. The predictive capabilities of DeepSeek enable your business to anticipate market trends thus enabling proactive decision-making.

5. Automation of Repetitive Tasks

DeepSeek helps automate time-consuming repetitive tasks that include social media scheduling and customer inquiry response. DeepSeek automation allows you to allocate your time toward strategic planning and creative thinking.

Real-Life Examples of DeepSeek OpenAI in Action

Let’s look at some real-world scenarios where DeepSeek OpenAI can make a difference:

E-commerce Store: DeepSeek enables online stores to examine customer reviews which reveals frequent customer grievances. Their analysis helps them enhance their products while developing specific marketing initiatives.

Social Media Manager: Social media managers use DeepSeek to create compelling captions and hashtags for their social media posts while the platform helps them determine successful content types. The tool helps users understand which types of content deliver the best results so they can modify their approach.

Small Business Owner: The website blog posts written through DeepSeek help the small business owner save significant amounts of time. Through this platform they generate customized email marketing initiatives which enhance customer retention.

Marketing Agency: DeepSeek enables marketing agencies to generate thorough reports by analyzing data from numerous clients through its system. The agency uses the data analysis to produce superior outcomes which enable them to excel in their competitive field.

Challenges and Limitations

While DeepSeek OpenAI is incredibly powerful, it’s not perfect. Here are a few challenges to keep in mind:

Dependence on Data: The quality of DeepSeek’s output depends on the quality of the data you provide. Garbage in, garbage out!

Lack of Human Touch: DeepSeek's content creation capability exists alongside its inability to replicate human emotional touchpoints in writing.

Learning Curve: Using any new tool requires users to overcome an initial learning process. Learning to utilize DeepSeek efficiently requires a period of complete understanding.

Cost: DeepSeek advanced AI tools present high costs for users with specific requirements.

How to Get Started with DeepSeek OpenAI

Ready to give DeepSeek OpenAI a try? Here’s how to get started:

Sign Up: Create an account at the DeepSeek website to begin. Platforms typically allow new users to experience free trial or demonstration features as a basis for learning their tools.

Define Your Goals: What objectives do you want to accomplish through DeepSeek? Clear objectives about content creation data analysis and customer engagement will help you maximize your use of the tool.

Explore Features: Spend a few moments to investigate all features and capabilities of DeepSeek. Perform multiple tasks to determine which ones provide your optimal results.

Integrate with Your Workflow: DeepSeek enables integration with multiple tools including CRM systems and email marketing platforms and social media scheduling tools.

Monitor and Adjust: When using DeepSeek monitor the results to enable necessary adjustments. The more time you spend using its capabilities the better you will become at accessing its full potential.

The Future of DeepSeek OpenAI

DeepSeek OpenAI holds an exciting path into the future. AI technology's future development will bring us progressively enhanced capabilities and features. Future versions of DeepSeek OpenAI could develop capabilities to generate video content while designing graphics and autonomously managing complete marketing campaigns.

Final Thoughts

DeepSeek OpenAI functions as more than a tool because it represents a transformative solution for digital marketing alongside other fields. The system allows businesses to achieve better results through automated processes while creating valuable insights and expanded creative possibilities. DeepSeek serves marketers at every experience level to help them reach their objectives at accelerated speeds while boosting operational efficiency.  Visit Eloiacs to find more about AI Solutions.

[niconiconwo]

Got a little more caught up on the DeepSeek thing. I still am very wary of LLM chat bots etc, but it's hilarious that for essentially pennies a Mainland AI outperforms all these billion dollar projects simply by..using common sense optimisations and search fencing.

The real driving force of the US panic over this development is obviously the fact that if an auditable and open-source LLM overtakes intelligence backed CIA plants then their dream panopticon will die.

A necessary reminder that OpenAI is neither a non-profit nor is it very open in any meaning of the term. They also are partnered with Microsoft, cooperate with the US military, and are funded by DARPA.

[idigitizellp21]

DeepSeek's Disruption in AI: How a Chinese Startup is Challenging Global Tech Giants

The artificial intelligence (AI) landscape is witnessing a paradigm shift as emerging players challenge the dominance of long-established tech giants. Among these disruptors, DeepSeek, a Chinese AI startup has rapidly positioned itself as a formidable competitor, pioneering advancements that rival the industry's most powerful models. By delivering high-performance AI solutions at a fraction of the cost incurred by its Western counterparts, DeepSeek is redefining the trajectory of AI innovation. 

⁠The DeepSeek: Technological Breakthroughs⁠

DeepSeek has garnered significant attention with its R1 reasoning model. This sophisticated AI system matches the capabilities of models developed by industry leaders such as OpenAI yet is built with a markedly lower financial investment. This breakthrough has positioned DeepSeek as a pivotal player in the global AI race, driving efficiency and accessibility in artificial intelligence development.

One of the most strategic applications of DeepSeek’s R1 model is within China’s burgeoning electric vehicle (EV) industry. Leading automotive manufacturers, including BYD, Geely, and Great Wall, have integrated this AI into their vehicle software, enhancing smart driving features such as autonomous parking and highway navigation. This move signifies a crucial step in China’s efforts to surpass competitors like Tesla in the smart vehicle domain.

Implications for the Global AI Market⁠

DeepSeek’s rise is indicative of a larger shift in AI leadership. Traditionally, AI innovation has been concentrated within a few Western firms with extensive computational resources and billion-dollar investments. However, DeepSeek’s ability to produce state-of-the-art AI models with leaner resources challenges this monopoly, democratising access to cutting-edge technology. This evolution is reminiscent of broader AI transformations, such as the evolution of chatbots in business from FAQ bots to AI sales agents, where intelligent automation has redefined customer interaction and business operations.

The market response to this disruption has been substantial. Investors are increasingly drawn to cost-effective AI solutions, prompting a shift in venture capital allocation towards lean AI startups. Additionally, DeepSeek’s emergence coincides with a period of volatility in the AI sector reflected in significant valuation adjustments among leading chipmakers and AI firms.

⁠Challenges and Ethical Considerations⁠

Despite its technological prowess, DeepSeek faces notable hurdles, particularly concerning data privacy and regulatory scrutiny. The company has encountered resistance in international markets, with regulatory bodies raising concerns over data security, potential surveillance risks, and compliance with global AI governance standards. Notably, New York state has banned DeepSeek’s AI within government networks, citing apprehensions about data harvesting and foreign interference.

These developments underscore the growing intersection between AI innovation and geopolitical considerations. As AI continues to shape critical infrastructure, governments and enterprises must balance technological adoption with safeguarding security interests.

⁠The Future of AI: A Decentralised Landscape?⁠

DeepSeek’s trajectory signals a broader transformation in AI development, one that challenges the traditional notion that cutting-edge advancements necessitate vast financial and computational resources. The startup’s success suggests that a decentralised AI landscape, where innovation is no longer confined to a handful of dominant players, is becoming an increasingly tangible reality.

However, with this decentralisation comes a new set of responsibilities. As AI capabilities proliferate, ensuring ethical deployment, regulatory compliance, and alignment with global data privacy standards will be paramount. Companies leveraging AI solutions will need to remain vigilant, selecting technologies that align with their long-term strategic goals while adhering to ethical best practices. 

At iDigitize, we recognise the critical role AI plays in shaping the future of business and technology. As a leading marketing agency, we empower brands to harness AI-driven strategies that optimise engagement, efficiency, and growth.

To stay ahead in this dynamic digital landscape, businesses must adopt a forward-thinking approach to AI integration. Contact the best Digital Marketing Agency in Mumbai today to explore how cutting-edge AI solutions can elevate your brand’s competitive edge and redefine your market presence.

[linjames41]

If, I mean if, AI Could Grant One Wish, What Would You Want It To

AI is becoming a core part of our daily lives, and companies continue to introduce more intelligent AI models. From the breakout success of Deepseek to the recent launch of Grok 3, the so-called "smartest AI on Earth." These AI models are constantly reshaping our understanding of technology. While we often think of AI as all-knowing and omnipotent, when I take a step back and reflect, if I could have one wish granted by AI, what would it be?

AI and Its Ever-Evolving Impact

Today, there are countless “AI learning courses” available online. For example, courses on using AI for stock trading, predicting the top 10 most depreciating assets… People have pinned their hopes of wealth onto AI, believing it can guide them toward a brighter financial future. For students, AI has become an invaluable learning assistant, helping with tasks from organizing research to writing essays, significantly improving productivity. Across various industries, AI is playing a pivotal role in streamlining processes and enhancing efficiency.

However, for the average person, the primary use of AI is still limited to retrieving information or processing text and images. Most of the time, AI lives as an app on our phones or computers, waiting to be called upon when needed.

If AI Could Fulfill One Wish: What Would My Ideal AI Be Like?

If I were to design the perfect AI, I would envision something like Doraemon’s "4D pocket," where I could have access to all kinds of gadgets—things like a “door to anywhere,” a “bamboo-copter,” or even “memory bread.” While these ideas sound far-fetched in today’s world, they remind me of how humans from centuries ago dreamt of space travel or exploring the deep sea. Fast forward to today, and we’ve made those dreams a reality.

To me, AI is like a key that unlocks a door to our dreams. Perhaps, with the help of AI, I could one day invent airplanes or rockets, and I could communicate with AI to explore my ideas and gain new knowledge—bringing me one step closer to turning my dreams into reality.

Exploring AI's Boundless Potential

Our imagination is the only limit when it comes to AI. We often wonder just how far it can go, what new boundaries it can push. I think the tool that best integrates AI into our daily lives right now is the smartphone. With AI integrated into the phone’s system, I can snap a photo of my meal and have AI instantly analyze its calorie count—a particularly useful feature as I’m currently trying to lose weight.

Through AI’s real-time translation feature, I can easily communicate with friends from around the world without worrying about language barriers. This simple functionality has already begun to bridge the gap between cultures and create global conversations that were once impossible.

XXAI's New Features: Bringing AI to the Forefront

Recently, XXAI launched the “Chat” feature on its website, allowing users to seamlessly switch between 15 leading AI models for direct conversations. Not only that, but the upcoming “Bots” feature will let users engage in conversations with preset characters, such as their favorite celebrity or a distant friend. XXAI is aiming to enhance its user experience by providing more practical features that make the power of AI more accessible and interactive.

How Will AI Continue to Shape Our Lives?

AI is already making its mark on various aspects of our lives, whether it's work, education, entertainment, or even day-to-day tasks. With AI advancing at an unprecedented pace, it’s exciting to imagine how it will continue to evolve and shape the future.

Will AI redefine our understanding of life, work, and even our personal aspirations? As AI continues to improve, it has the potential to change how we interact with the world around us. What new possibilities will emerge, and how will we adapt to this new technological frontier?

[thetechpulsz]

Mastering AI Article Writing in 2025: A Global Playbook for the Next Era of Content

By TechPulsz, AI Content Strategist The art of writing is no longer confined to human hands. As AI article writing tools evolve from basic text generators to strategic content partners, mastering this technology has become a non-negotiable skill for creators, businesses, and nations vying for digital dominance. From New York to New Delhi, Beijing to Berlin, and Dubai to Delhi, AI is reshaping how stories are told, brands are built, and ideas are exchanged. Let’s explore how to harness these tools ethically and effectively across key global hubs.

The AI Article Writing Revolution: By the Numbers

- 70% of Fortune 500 companies now use AI for routine content tasks. - 181 million+ monthly users rely on platforms like Grammarly for real-time writing assistance. - 40% of retail transactions in India are mediated by AI sales bots .

Regional Roadmaps: AI Article Writing in 2025

1. USA: Leading the Agentic AI Charge Silicon Valley’s AI tools like Jasper and Copy.ai now autonomously draft press releases, SEO blogs, and even technical white papers. The focus? Agentic AI – systems that don’t just write but strategize. For instance, platforms like Frase analyze competitor content gaps and auto-generate data-driven articles optimized for Google’s E-E-A-T guidelines. Key Trend: Hybrid workflows where AI handles 80% of drafts, while humans refine tone and inject creativity. MIT Sloan reports 58% of U.S. firms now see “exponential productivity gains” from such models. 2. India: Vernacular Content at Scale With 30% of India’s internet users preferring regional languages, tools like Rytr and SEO.ai dominate. These platforms generate culturally nuanced articles in Tamil, Bengali, and 50+ other languages while avoiding ethical pitfalls like digital colonialism in gig economy automation 110. Challenge: Balancing efficiency with authenticity. A draft AI Ethics Code mandates bias audits for tools deployed in sectors like education and healthcare. 3. China: Specialized Industry Models Chinese labs prioritize vertical AI writers – tools trained on industry-specific data. DeepSeek V3, for example, generates pharmaceutical research papers and manufacturing SOPs with 98% accuracy. However, U.S. chip restrictions have spurred innovation in homegrown alternatives like Huawei’s Ascend-powered platforms. Stat: 75% of Chinese enterprises now use generative AI for content, up from 55% in 2024. 4. Europe: Regulation-Driven Innovation The EU’s AI Act forces tools like Writesonic to offer “light versions” with watermarked AI content. Meanwhile, Germany’s planned AI Data Center aims to train GDPR-compliant models for sectors like finance and healthcare. Tool Spotlight: StorPool optimizes energy use in AI writing workflows, cutting LLM carbon footprints by 35% 5. Middle East: Building Sovereign AI Writers The UAE’s MBZUAI collaborates with NVIDIA to develop Arabic LLMs like Jais 2.0, which preserve linguistic heritage while generating marketing content for Dubai’s tourism sector. Saudi’s NEOM smart city uses AI to auto-translate technical manuals into 12 languages for its global workforce. Mastering the Tools: 2025’s AI Writing Stack - SEO.ai: Generates multilingual, SERP-optimized articles with real-time keyword analysis. - Grammarly: Enhances clarity and adapts tone for diverse audiences – crucial for global teams. - LangChain: Builds custom AI writers that pull data from proprietary databases (e.g., legal precedents or medical journals). - Leonardo AI: Rapidly prototypes AI-generated video scripts paired with articles for TikTok/Instagram. Ethical Frontiers: The Global Debate - Bias Mitigation: Tools like Writerly now flag gendered language and cultural stereotypes in real-time. - Job Displacement: While AI creates roles in prompt engineering, 42% of writers fear redundancy. - Deepfake Prose: India’s draft laws require disclosing AI use in news articles to combat misinformation. Future-Proofing Your Skills - Learn Prompt Engineering: Craft commands like “Write a climate tech blog in Hinglish, citing 2025 UAE solar initiatives” . - Adopt Hybrid Workflows: Use AI for research/drafts, then add anecdotes and local idioms. - Master Cross-Platform Tools: Combine Zapier automations with ChatGPT for end-to-end content pipelines. The Road Ahead: 2026 Predictions - Hyper-Personalization: AI will auto-generate 10 article variants for different reader personas. - AI Avatars: Platforms like Synthesia will produce video articles voiced by digital clones. - Regulatory Wars: Expect diverging standards between China’s industry-focused rules and Europe’s ethics-first approach. Also Read: AI News in 2025: Global Breakthroughs Reshaping Industries from Silicon Valley to Shanghai Read the full article

[blackholerobots]

Bloomberg: Grok-3: Elon Musk's xAI Unveils New AI Model to Rival ChatGPT, DeepSeek

https://www.bloomberg.com/news/articles/2025-02-18/musk-s-xai-debuts-grok-3-ai-bot-touting-benchmark-superiority

[timestab]

Baidu and OpenAI Launch Free AI Chatbots in Response to DeepSeek

Baidu, the Chinese internet search giant, will offer its advanced AI chatbot, Ernie Bot, for free starting April 1. This includes premium features like AI painting, and the service will be available to both mobile and desktop users. Baidu’s move comes amid rising competition in the AI market, especially following the success of startup DeepSeek’s AI models. In response, OpenAI’s CEO Sam Altman…

[womaneng]

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✨Watch DeepSeek AI bot respond to question about China 🤨 An AI-powered chatbot by the Chinese company DeepSeek has quickly become the most downloaded free app on Apple’s store, following its January release in the US. The app has sparked chaos in the US markets and raised questions about the future of America’s AI dominance.

[matildaschmidttrades]

AI Disruption: How BYD and DeepSeek Are Reshaping Markets

Markets are constantly evolving, and those who anticipate change often come out ahead. At ORION Wealth Academy, I’ve learned that staying ahead isn’t just about reacting to price movements — it’s about understanding how technological shifts create new opportunities. Right now, AI is reshaping industries, and the latest shake-up comes from China’s BYD and DeepSeek, posing a serious challenge to Tesla’s dominance in autonomous driving.

Disruptive Innovation: AI’s Power Beyond Trading

What makes this partnership significant isn’t just the competition — it’s the business model shift. While Tesla still charges a premium for Full Self-Driving software, BYD is offering its AI-powered “God’s Eye” system as a standard feature. This mirrors what’s happening in trading: once exclusive, high-cost AI tools are becoming more widely available, leveling the playing field for both retail and institutional traders.

AI isn’t just an efficiency booster anymore — it’s a market disruptor. Whether it’s DeepSeek’s AI revolutionizing self-driving, or machine learning models optimizing trade execution, those who adapt to these AI-driven changes will stay ahead, while those who resist may fall behind.

We’ve already seen AI-powered trading bots and automated strategies redefine financial markets. But as AI continues evolving, traders must think beyond price charts — we need to anticipate how AI-driven automation impacts entire industries. The fact that BYD can integrate cutting-edge AI at scale suggests that more industries will follow, affecting everything from supply chains to global economic trends — all of which ultimately influence the markets we trade.

At ORION Wealth Academy, I’ve learned that trading success isn’t just about making the right moves — it’s about seeing the bigger picture. And right now, the big picture is clear: AI is no longer just a tool — it’s the market itself.

The question is, are we prepared to trade the future? 🚀