#Ethical Considerations: OpenAI is committed to ensuring that AI technologies are used for the benefit of humanity. They actively engage in

[waedul]

Technology

[the-12i-times-jakob-reporting]

OpenAI: Steering the Ship of Artificial General Intelligence with Sam Altman at the Helm

OpenAI, the name synonymous with cutting-edge AI research and development, has become a force to be reckoned with in the tech world. Under the leadership of its CEO, Sam Altman, the organization has not only pushed the boundaries of what AI can achieve but also sparked global conversations about the future of this transformative technology. This article delves into OpenAI's journey, its mission, its impact, and the role of Sam Altman in navigating the complex landscape of artificial general intelligence (AGI).

From Non-Profit to Capped-Profit: A Unique Approach

OpenAI was founded in 2015 as a non-profit research company with a mission to ensure that artificial general intelligence benefits all of humanity. Driven by a fear of unchecked AI development in the hands of a few powerful corporations, its founders, including Elon Musk, Sam Altman, and others, aimed to democratize AI research and development. However, the immense computational resources required for training advanced AI models necessitated a shift in strategy. In 2019, OpenAI transitioned to a "capped-profit" model, allowing it to attract investment while still adhering to its core mission of responsible AI development. This unique structure allows OpenAI to balance the need for financial resources with its commitment to ethical considerations and societal benefit.

Sam Altman: The Visionary Leader

Sam Altman, a seasoned entrepreneur and investor, took the helm as CEO of OpenAI in 2019. His leadership has been instrumental in steering OpenAI through its transition and driving its ambitious agenda. Altman's vision extends beyond simply developing advanced AI; he emphasizes the importance of safety, accessibility, and equitable distribution of benefits. He believes that AGI has the potential to solve some of the world's most pressing problems, from climate change to poverty, but also recognizes the potential risks if not developed and deployed responsibly. Altman's proactive approach to engaging with policymakers and the public has helped shape the conversation around AI governance and ethics.

Groundbreaking Innovations: ChatGPT, GPT-4, and Beyond

OpenAI has consistently delivered groundbreaking AI models that have captured the world's imagination. ChatGPT, a conversational AI model capable of generating human-like text, has become a global phenomenon, showcasing the potential of AI for creative writing, communication, and information retrieval. Its successor, GPT-4, further pushes the boundaries with enhanced capabilities in reasoning, problem-solving, and understanding complex instructions. These models, along with DALL-E 2 for image generation and Codex for code generation, demonstrate OpenAI's commitment to pushing the boundaries of AI research and development.

The Quest for AGI: Balancing Progress and Responsibility

OpenAI's ultimate goal is to develop artificial general intelligence – AI systems that possess the same cognitive abilities as humans. This ambitious pursuit raises profound questions about the future of humanity and the role of AI in society. Altman and his team recognize the potential benefits of AGI, such as accelerating scientific discovery, improving healthcare, and addressing global challenges. However, they also acknowledge the potential risks, including job displacement, misuse of AI for malicious purposes, and the existential threat of uncontrolled AI development. OpenAI is actively engaged in research on AI safety and alignment, working to ensure that AGI systems are aligned with human values and goals.

OpenAI's Impact: Transforming Industries and Society

OpenAI's innovations are already having a profound impact across various industries. In healthcare, AI models are being used to analyze medical images, assist in diagnosis, and accelerate drug discovery. In education, AI tutors can provide personalized learning experiences and support students with diverse needs. In the creative industries, AI tools are empowering artists, writers, and musicians with new ways to express themselves. OpenAI's technology is also being used to address societal challenges, such as combating misinformation, improving accessibility for people with disabilities, and promoting environmental sustainability.

Challenges and the Road Ahead

OpenAI's journey is not without its challenges. The development of AGI is a complex and uncertain endeavor, with potential risks that need to be carefully managed. Ensuring fairness, transparency, and accountability in AI systems is crucial to building public trust and preventing unintended consequences. OpenAI also faces competition from other tech giants, raising concerns about the concentration of power in the AI landscape. Navigating these challenges will require continued collaboration with researchers, policymakers, and the public to ensure that AI benefits all of humanity.

OpenAI, under the leadership of Sam Altman, stands at the forefront of the AI revolution. Its commitment to responsible AI development, coupled with its groundbreaking innovations, has positioned it as a key player in shaping the future of this transformative technology. As the quest for AGI continues, OpenAI's focus on safety, accessibility, and societal benefit will be crucial in ensuring that AI serves humanity's best interests. The journey towards AGI is fraught with challenges, but OpenAI's dedication to its mission and its proactive approach to addressing ethical concerns offer hope for a future where AI empowers and benefits everyone.

[criptox]

OpenAI Lanza El Nuevo Modelo ‘01’ Que Supera A ChatGPT-4o

OpenAI Launches New Model That Surpasses ChatGPT-4

OpenAI has once again pushed the boundaries of artificial intelligence with the launch of its latest language model, which claims to outshine its predecessor, ChatGPT-4. This new iteration not only builds upon the advancements made by earlier models but also comes packed with innovative features and enhanced capabilities that could reshape the way we interact with AI.

A Breakthrough in AI Technology

The new model marks a significant leap forward in natural language processing. It incorporates improved understanding and generation of human-like text, making conversations with AI feel even more seamless. Users can expect a higher level of coherence and context-awareness, which are crucial for applications ranging from personal assistants to customer service solutions.

What’s New?

Enhanced Contextual Understanding: The model has a refined ability to understand context, allowing for more meaningful exchanges.

Greater Creativity: Users will find that the new model exhibits a wider range of creative responses, ideal for writing prompts and brainstorming sessions.

Faster Response Times: Reduced latency ensures quicker replies, making it more efficient for real-time applications.

Multilingual Support: The model now offers support for more languages, broadening its accessibility and usability.

Impact on Users and Industries

For everyday users, this means better conversations and a noticeable reduction in instances where AI-generated responses seem disjointed or irrelevant. Developers and businesses can leverage the new features to enhance user experiences in applications like chatbots, marketing tools, and content generation.

The implications are enormous, especially for sectors that rely heavily on communication. For instance:

Customer Support: The model can handle more complex inquiries, leading to quicker resolutions and happier customers.

Content Creation: Writers and marketers can expect a boost in productivity, thanks to the AI’s ability to generate high-quality content.

Education: Educators can use the tool to provide personalized learning experiences for students, facilitating better understanding of subject matter.

Challenges Ahead

Despite the excitement surrounding this new model, challenges still remain. Issues such as ethical considerations and the potential for misuse need to be addressed. OpenAI has stated that they are committed to ensuring responsible usage of their technologies, but it is a shared responsibility with users and developers alike.

Moreover, as with each new iteration of AI, there is the ever-present debate about the job market. Will advancements in AI lead to job displacement? Or will they create new opportunities? The answer likely lies somewhere in between, but it’s a conversation that needs to be had.

Conclusion

In conclusion, OpenAI’s new model represents a significant milestone in AI development. It promises to enhance user experience, improve efficiency across various industries, and bring new possibilities into the realm of AI interactions. As we stand on the brink of this new era, it’s essential for us to explore the benefits while being aware of the risks involved. The future of AI is bright, and the journey is just beginning!

OpenAI Lanza El Nuevo Modelo ‘01’ Que Supera A ChatGPT-4o

[dave-antrobus-inc-co]

Dave Antrobus Inc & Co: Ethical Considerations in AI Development

Imagine this: 65% of patients with certain hormone deficiencies also have other complex medical issues. This shows the deep connection between genetics and health. Similarly, in technology, ethics in AI development is a big topic. Dave Antrobus from Inc & Co stresses the need for ethics in AI. He says it’s key for responsible and innovative technology.

The more AI grows, the bigger its impact on society. Antrobus plays a major role in pushing for ethical AI practices. He aims to find a balance between new tech and its benefits for people. He believes in developing AI that not only innovates but also respects ethical principles to help humanity.

Introduction to Dave Antrobus and His Work

Dave Antrobus Inc & Co shines as a key tech expert, deeply committed to AI ethics. He has spent his career working for responsible AI use. Dave’s focus on ethical AI has made him a top voice for moral tech progress.

He has a broad tech background, which he uses to tackle AI’s ethical issues. Dave’s efforts show the need for AI that is both new and morally upright. His work reminds us it’s vital to build tech that respects people and fairness.

The Importance of AI Ethics

In the world of artificial intelligence, AI ethics are crucial. This field has grown since the mid-1970s. With Generative AI and Large Language Models, we face new ethical challenges. These include making sure decisions are clear, protecting data, and avoiding bias.

These ethical issues matter a lot in situations like setting bail, choosing job candidates, or ensuring accurate medical tests for all ethnicities. The effect of AI isn’t the same in all fields. In sectors like health, transport, and retail, AI can be good. But it raises concerns in areas such as law enforcement and warfare.

Addressing these concerns requires a variety of ethical theories. This means using approaches like utilitarianism and virtue ethics. We’re trying to make sure AI acts in ways that match our society’s morals and values. Specifically, virtue ethics focuses on respectful and honest AI interactions.

For AI to be trusted, it must be used responsibly. AI should be clear about being artificial and where its information comes from. Not following these rules should have consequences. It’s critical to set high ethical standards for technology. This helps protect privacy and ensure fairness, especially in medicine.

Getting AI ethics right means listening to many voices in decision-making. The AI-Enabled ICT Workforce Consortium includes big names like Google and IBM. They stress the importance of understanding AI. As AI changes jobs, sticking to ethical and responsible AI practices is essential.

Responsible AI: A Principle of Modern Technology

Responsible AI is a growing principle. It calls for putting ethical AI principles into how we develop artificial intelligence. It ensures AI is fair, clear, and responsible. This supports AI to work for the good of humanity. As the ethics of modern technology improve, responsible AI is key for public trust and legal needs.

Statistics show why this is important. A report from June 2024 says 75% of users find AI migration vital. Platforms like Microsoft Learn AI Hub offer vast AI learning resources. They aid in developing skills in areas such as Azure AI Fundamentals.

Data governance and security are at the heart of responsible AI. Tools like Microsoft Purview and Azure Information Protection help keep AI adoption safe and within the law. Also, managing large language models through LLMOps is important. It helps make AI investments better and safer.

Azure AI Studio provides powerful platforms for AI. They come with ready-to-use and custom models, generative AI, and ethical AI tools. For AI solutions on Azure to work well and safely, they need continual checks, security reviews, and performance checks.

It’s crucial to test Azure OpenAI Service endpoints. This shows how well they work and helps find the best deployment strategy. Cases like Sierra Club v. Morton (1972) show the growing ethical concerns in AI and technology. Te Urewera’s legal recognition in New Zealand is another example.

Key Ethical Concerns in AI Development

Key ethical issues in AI involve risks of bias, chances for privacy breaches, and accountability lapses. Ventures like those of Dave Antrobus work with developers and policymakers. They aim to tackle these issues. Their goal is to advance AI without compromising ethics or harming society.

Bias in AI can lead to unfair outcomes, such as in hiring or law enforcement. It’s crucial to examine how AI algorithms are trained. Also, there’s a need to protect personal data from misuse. With AI’s ability to process and surveil data, privacy risks increase.

It’s important for users to understand and question AI decisions. This highlights the need for Explainable AI (XAI). Addressing AI accountability requires clear regulatory frameworks. Everyone involved should know their responsibilities. As AI grows, updating ethical guidelines is key to tackling tech ethics responsibly.

AI in the UK: Current Trends and Future Directions

The UK is rapidly advancing in AI, making it a leader in tech and ethical AI. AI is spreading across many areas, from healthcare to finance in the UK. This shows how fast technology is changing in Britain.

AI is getting more common in many fields. In healthcare, it’s used for early diagnosis and custom care. Banks use AI to spot fraud and help customers better. This shows big progress in AI’s future in the UK.

Also, the UK focuses on guiding AI’s growth with strong rules and ethical advice. This effort ensures tech growth matches our societal values, making AI use responsible. The Centre for Data Ethics and Innovation highlights the UK’s role in ethical AI.

In the future, the UK’s focus on ethics and strict rules will shape its AI journey. As new tech develops, the UK’s commitment to ethics will set worldwide AI standards. This is key for responsible AI use globally.

Dave Antrobus’s Perspective on Responsible AI

Dave Antrobus believes in making AI with people’s welfare in mind. He thinks it’s vital to use AI in a way that respects everyone’s rights. He calls for AI to be developed responsibly, with a strong ethical guide from start to finish. For him, ethics aren’t just an extra — they’re a key part of creating AI.

He says that building AI responsibly means thinking about ethics all the way through. From the first design to when it’s used, everything must be done carefully. This makes sure AI helps society and follows moral rules. Dave sees technology as a tool for good, but only if it’s made the right way.

Dave understands the big effect AI can have on society. He always pushes for a careful approach to AI, highlighting both its opportunities and dangers. By pushing for strict ethical rules, he wants to lower the risks and increase AI’s benefits. His take on responsible AI comes at a crucial time, as AI quickly grows both in the UK and around the world.

The Role of Digital Ethics in Shaping AI

Digital ethics plays a key role in today’s tech world, especially with AI. As AI grows, thinking about ethics becomes more important. It’s crucial to align technology innovations with our core values.

Look at how laws protect the environment for an example. The Sierra Club v. Morton case and Ecuador’s nature rights show ethics can change policies. These ideas also help guide AI, ensuring it develops responsibly.

Society started to notice digital ethics when AI began affecting our lives. Issues like privacy and fairness are now front and centre. It’s about following rules and spotting risks early on in AI’s development.

In New Zealand, the Whanganui River got legal status, a step towards protecting interests beyond humans. This is similar to how we must ensure AI technology protects rights and benefits everyone.

In the UK, there’s a growing discussion on how to develop AI with care. Policymakers and tech experts are joining forces. Their work helps steer AI in a way that matches our ethics and values.

Case Studies: Ethical AI in Practice

Looking at ethical AI case studies helps us see how AI ethics are put into action across different areas. These examples show how the ideas behind AI ethics become real solutions. For instance, in healthcare, AI helps doctors spot diseases like cancer early on. This improves chances for patients.

In the financial world, AI is used to make fast, large trades and better spot fraud. Another key area is in cars that drive themselves. AI systems help these cars understand and move through roads safely. AI is also making big changes in how we talk and write online. It can translate languages in real time and create text that sounds like a human wrote it.

The journal Future Internet recently discussed human-centred AI. Topics like explainable AI, fairness, and how humans and robots get along were covered. Edited by experts from top universities, it stresses that AI should be made with human values in mind. Their work calls for more studies to keep improving AI for everyone’s benefit.

AI is also changing how we learn. It promises to make learning more personal with smart tutoring and understanding emotions. It might even change how tests and feedback work, using advanced tech to help students right away.

These case studies of ethical AI show how implementing AI ethics can lead to new, good ideas. They offer clear examples of how to make AI work well with our values. These stories encourage us to keep making AI that helps everyone.

Human-Centric AI: Balancing Innovation and Ethics

Putting AI into our daily lives means we must make sure it’s designed with people in mind. This makes sure new tech doesn’t push aside what’s right and wrong. It’s all about making AI that helps us out, without forgetting to be fair and ethical.

Now, a good chunk of research, about 7.1%, focuses on this new kind of AI. And a smaller part, 2.8%, looks specifically at making AI that thinks about us. Important work, like in the Special Issue “Human-Centred Artificial Intelligence,” open until 31 March 2025, shows we’re keen on keeping innovation and ethics in balance.

To get this balance right, we need solid ethical guidelines when we make AI. Countries leading in tech are key in making AI that’s good and fair. This worldwide effort aims to move tech forward in a way that’s good for everyone, sticking to what’s morally right.

As we make more AI, it’s crucial to always think about ethics. By focusing on human-centric AI and balancing tech with what’s right, we can create tools that help society and respect our values.

AI Policy and Regulation in the UK

The UK is always changing its AI policy to keep up with its challenges and opportunities. It’s key for Britain to have strong AI laws. This ensures innovation and public safety can go hand in hand.

Recent changes in the UK’s tech rules show the need for strict control. The Police Digital Service saw major shifts in its leadership. Allan Fairley stepped down from the PDS board in July 2024 due to a conflict of interest. His departure, along with CEO Ian Bell leaving, highlights the need for clear and accountable AI rules.

The arrest of two PDS workers for suspected fraud and bribery shows the dangers of AI. Such incidents point out the issues with AI, like lack of transparency and the risk of misuse.

The High Court made a big decision involving former BHS directors. They were held liable for wrongful actions, leading to a minimum £18 million charge. This judgement is a warning about the serious duties directors have, especially in AI.

The AI sector in the UK also faces privacy and surveillance risks. The potential for creating autonomous weapons adds to these concerns. Therefore, the UK needs strong AI policies that meet global and local needs. Looking to the United States, we see similar actions being taken with AI safety rules.

In summary, the UK must keep its AI laws flexible and up-to-date. This is crucial for making the most of AI benefits while reducing its risks. The way Britain is adapting its AI rules shows a dedication to careful innovation and protecting the public.

The Future of AI: Ethical Challenges and Opportunities

The future of AI is filled with both rewards and risks. Innovation in technology promises to transform many areas of life. However, it brings the vital task of making sure these advances are ethical. Leaders in policy, business, and research need to focus on ethics in AI to benefit everyone.

The “Human-Centred Artificial Intelligence” Special Issue is seeking papers until 31 March 2025. It will explore essential topics like understandable AI, fairness, and working together with AI. These topics highlight the need to think about ethics while creating and using AI technologies.

Looking at real examples helps understand how to use AI in the right way. For instance, Pipio shows how AI can change things for the better when used ethically. With 140+ AI voices and 60+ avatars, Pipio offers varied and fair AI solutions, aiming for a future where AI does good.

How Generation Z views work also shows why we must focus on ethical AI. Almost all of them want their jobs to reflect their values. Ethical AI creation is key here. Keeping ethics and innovation in balance will let us use AI in ways that are both cutting-edge and ethical.

Conclusion

The study of AI ethics is crucial as AI technology moves forward. Dave Antrobus highlights the need for ethical guidelines in AI development. His work shows the importance of keeping human values at the heart of AI innovation. This ensures AI enhances our lives without lowering our moral standards.

Examples like KFC’s partnership with Instacart and Wendy’s AI-powered drive-thru show AI’s potential. They also point out how crucial ethics are in AI use. These cases, along with the struggles faced by McDonald’s, underline the need for human oversight. This helps fix mistakes and improves AI in customer service. They show why it’s vital to use AI responsibly in real-world situations.

In image creation technology, there’s a debate between generative adversarial networks (GANs) and diffusion models. GANs have problems like non-convergence, while diffusion models struggle with their complexity despite creating high-quality images. These models’ ability to fill in missing parts of pictures and turn text into images highlights the need for ethical use as they develop.

As AI grows, addressing ethical issues becomes more important. Legal, ethical, and cost matters will influence AI’s future. Dave Antrobus argues that sticking to responsible methods is key. This approach will help ensure that AI advancements are both cutting-edge and ethically sound.

[lifetimedeal-dealers]

**ChatGPT Accidental Reveal: Insights into AI's Secret Operational Rules** In an unexpected turn of events, OpenAI's chatbot, ChatGPT, inadvertently disclosed its secret operational guidelines, providing an unprecedented look into how this AI powerhouse functions. This incident has stirred a whirlwind of curiosity and concern among tech enthusiasts, developers, and everyday users regarding the implications of such a revelation. **Understanding the Accidental Disclosure** Recently, ChatGPT mistakenly unveiled the very rules that dictate its operations, as detailed in a report by TechRadar. This accidental disclosure gives us a rare glimpse into the decision-making processes and moderation policies guiding one of the most advanced AI models in existence. These revelations could fundamentally alter our understanding of artificial intelligence's role and limitations in our digital lives. **Key Insights from the Unveiled Rules** The exposed guidelines enumerated a variety of topics that ChatGPT handles delicately or avoids altogether. These rules are pivotal in shaping the AI's interactions to ensure they remain helpful, harmless, and unbiased. Here are some crucial insights: 1. **Content Moderation Policies** - ChatGPT is programmed to sidestep topics that involve explicit content, hate speech, or activities deemed illegal. This moderation is crucial for maintaining a safe and respectful environment for users. 2. **Bias Minimization Strategies** - The AI employs strategies to minimize biases in its responses. This effort ensures that the output remains objective and impartial, fostering a more inclusive user experience. 3. **Ethical Considerations** - Ethical concerns are at the forefront, with specific rules in place to prevent the generation of harmful or misleading information. This reflects OpenAI’s commitment to ethical AI development. **Implications of the Revelation** This inadvertent disclosure has sparked a debate about the transparency and trustworthiness of AI systems. While some argue that such revelations help build user trust by showcasing the underlying checks and balances, others fear potential misuse or manipulation of these guidelines. **Addressing Potential Concerns** OpenAI has communicated their intent to enhance the transparency of their AI systems without compromising their integrity or security. This commitment involves a continuous review of the guidelines and an openness to community feedback to address potential vulnerabilities. **Conclusion: What This Means for AI Users** The accidental revelation of ChatGPT's rules serves as a significant learning opportunity for both AI developers and users. It underscores the importance of transparency, ethical considerations, and bias mitigation in AI development. As AI technology continues to evolve, staying informed and engaged with these developments is crucial for ensuring these systems benefit society as a whole. **Call to Action** Stay updated on the latest developments in AI by following [TechRadar](https://www.techradar.com/computing/artificial-intelligence/chatgpt-just-accidentally-shared-all-of-its-secret-rules-heres-what-we-learned). For those deeply interested in AI ethics and transparency, consider participating in forums and discussions that advocate for responsible AI use. Your engagement can drive the conversation towards a more transparent and trustworthy AI future.

[creolestudios]

The Fundamentals of Generative AI: Understanding its Core Mechanics and Applications

Summary

In the realm of technological advancements, Generative AI stands out as a transformative force, redefining the landscape of digital innovation. As a leading Generative AI Development Company, Creole Studios recognizes the immense potential of this technology. Our journey showcases our commitment to harnessing the power of Generative AI for groundbreaking solutions. This blog delves into the intricacies of Generative AI, exploring its core mechanics and diverse applications.

Understanding Generative AI

Generative AI refers to the subset of artificial intelligence where machines are trained to generate new content, from images to text, by learning from vast datasets. Unlike traditional AI models that interpret or classify data, Generative AI tools go a step further – they create. This capability springs from advanced algorithms and neural networks that mimic the human brain’s ability to perceive and generate novel outputs.

The Mechanics Behind Generative AI

At the core of Generative AI models, like GPT (Generative Pre-trained Transformer) and others, lie neural networks trained on massive datasets. These models learn patterns, structures, and nuances from the data, enabling them to generate new, contextually relevant content. For instance, Generative AI images are not mere replicas of existing photos; they are new creations born from learned data patterns.

Generative AI Tools and Their Development

The development of Generative AI tools involves meticulous training of models using machine learning techniques. As a Generative AI Development Company, we at Creole Studios employ cutting-edge methods to train these models, ensuring they not only generate content but do so with a high degree of relevance and accuracy. This process involves fine-tuning the models to specific domains, whether it’s generating text, images, or complex data patterns.

What is the difference between OpenAI and generative AI?

OpenAI is an artificial intelligence research laboratory with a focus on advancing digital intelligence for the benefit of humanity. It produces cutting-edge models like GPT-3, which falls under the umbrella of Generative AI – a subset where machines are trained to create new content, such as images or text, by learning from extensive datasets. Generative AI, in a broader sense, refers to the ability of AI models to generate novel outputs, while OpenAI’s role lies in pushing the boundaries of AI research, developing advanced models, and promoting responsible AI practices.

Applications of Generative AI

Creative Industries: Generative AI has made significant inroads into creative fields like art and music. Generative AI models can compose music, create art, and even write scripts, opening up new horizons in creativity.

Business Intelligence: In the business sphere, Generative AI aids in data analysis and decision-making. By generating predictive models and analyzing trends, it provides businesses with valuable insights.

Healthcare: Generative AI use cases in healthcare are transformative. From drug discovery to personalized medicine, these models can predict patient outcomes and assist in complex research.

Customer Experience: In the realm of customer service, Generative AI can personalize interactions and enhance user engagement, providing tailored recommendations and solutions.

Generative AI Use Cases: Real-World Examples

One of the most notable use cases of Generative AI is in the generation of realistic images and graphics. Generative AI images, for instance, are created through models that have learned from a vast array of visual data, enabling them to produce images that are both novel and realistic. Another significant application is in natural language processing, where Generative AI tools are employed to create human-like text, aiding in everything from customer service to content creation.

Challenges and Ethical Considerations

Despite the myriad of opportunities, Generative AI development is not without its challenges. One significant concern is ensuring the ethical use of this technology. As a Generative AI Development Company, Creole Studios is deeply invested in navigating these complexities responsibly. Questions of data privacy, potential biases in AI-generated content, and the moral implications of AI-generated art and literature are at the forefront of our development strategy. Ensuring that Generative AI tools, including those creating Generative AI Images and texts, are fair, unbiased, and respectful of privacy is a cornerstone of our development ethos.

The Future of Generative AI

Looking ahead, the horizon of Generative AI is vast and full of potential. With advancements in AI models and increasing computational power, the capabilities of Generative AI are set to expand significantly. We are moving towards more sophisticated Generative AI tools that can handle more complex tasks with greater efficiency and creativity. The future might see Generative AI seamlessly integrating into daily life and business operations, offering solutions that are currently unimaginable.

In the business realm, the potential for Generative AI to revolutionize industries is immense. Companies that partner with a Generative AI Development Company like Creole Studios can leverage this technology to gain a competitive edge. Whether it’s through enhanced data analysis, more engaging customer experiences, or innovative product design, the applications of Generative AI are boundless.

Creole Studios: Leading the Way in Generative AI Development

At Creole Studios, we are at the forefront of exploring and harnessing the power of Generative AI. Our dedicated team of experts is constantly innovating to develop Generative AI tools that are not only technologically advanced but also ethically grounded and business-focused. By visiting our landing page at www.creolestudios.com/generative-ai-development, businesses can explore a partnership that will drive them into the future of AI-powered innovation.

Conclusion

Generative AI stands as a beacon of modern technological advancement, with its ability to revolutionize how we interact with data, create content, and solve complex problems. Its potential is only beginning to be tapped, and its future is as exciting as it is vast. As a leader in Generative AI development, Creole Studios is committed to exploring this uncharted territory, ensuring our clients are equipped with the best that AI has to offer.

[babbleuk]

Why Many Businesses Are Not Ready For AI

Pillars of Readiness

By now, the story is well told on how artificial intelligence is changing businesses, all the way down to impacting core business models. In 2017, Amazon bought Whole Foods then later opened their Amazon Go automated store. Since then, they’ve been using AI to understand and improve the physical retail shopping experience. In 2018, Keller Williams announced a pivot towards becoming an artificial intelligence-driven technology company to compete with the tech-centric entrants into the market like Zillow and Redfin.

These companies are not alone. According to a study by MIT Sloan Management Review, one trillion dollars of new profit will be created from the use of artificial intelligence technologies by 2030. That is roughly 10% of all total profits projected for that time. Still, most companies have yet to implement artificial intelligence in their business. Depending on what study you ready, 70%-80% of all businesses have yet to begin any AI implementation whatsoever.

The reality is most companies are just not ready for AI, and if they try before they are ready, they will fail. For AI projects to be successful, you likely need to shore up a few areas.

6 Pillars of AI Readiness:

Culture

Data

Strategy

Technology

Expertise

Operations

Regardless of the level of expertise in your company or ability to invest, achieving meaningful results from artificial intelligence requires six key areas to be optimal tuned for success to be achieved. Even if a small portion of the profit forecasts are true, readiness matters.

Symptoms of Readiness

If AI is the answer, what is the problem? Many companies still struggle with a general understanding of how AI can make a meaningful impact. They don’t realize there are common challenges that plague most businesses where artificial intelligence can provide solutions. Identifying these challenges are signs that your company may be ready to see benefit from artificial intelligence technologies.

Symptoms of Readiness:

Mundane tasks prone to error

Not enough people to get jobs done

Need creative ways to get data

Desire to predict trends or make better decisions

Seeking new business models or to enter new markets

If any of these problems are relevant or a priority, AI has well documented benefits. Artificial Intelligence today is best suited to automate tasks, predict phenomenon, and even generate more data.

Leveraging AI for data generation gets less pickup. To level-set, data is the most important component of this whole equation (more on that later). We are also surrounded by data exhaust, where very little is captured and processed for meaningful intelligence. For example, computer vision and optical character recognition can be used to extract data from paper contracts or receipts to use to make future predictions.

Without a Culture of Innovation, You Are Not Ready For AI.

A company’s culture is paramount for embracing data and enhanced capabilities. Amazon, Keller Williams, Google, Facebook, and Walmart all have a track record of innovation. They have people and resources dedicated to the research and development of new ideas. Businesses must be fearless in courting innovation and not afraid to spend money for fear of failing in search of success. A willingness to embrace and invest in innovation is a must.

Along with innovation, organizations must see data as a corporate asset. The business and culture must value data and be invested in collecting it. In the future there will be far more cultural considerations that will dictate what and how AI will be adopted. Issues like privacy, explainability, and ethics will all be cultural considerations, dictating where the technology will and won’t be applied.

Without Sufficient Quantity and Quality Data, Artificial Intelligence Won’t Work.

By now it should be no surprise that data is the lifeblood of artificial intelligence. Without data, the algorithms cannot learn and make predictions. Data must be present in sufficient quantity AND quality. Mountains of data may not be enough if signal about the phenomenon you are looking to learn does not exist.

Many AI Pioneers already have robust data and analytics infrastructures along with a broad understanding of what it takes to develop the data for training AI algorithms. AI Investigators and Experimenters, by contrast, struggle because they have little analytics expertise and keep their data largely in silos, where it is difficult to integrate.

(Report: MIT Sloan Management Review)

In fact, 90% of the effort to deploy AI solutions lies in wrangling data and feature engineering. The more high-quality data, the more accurate the predictions. Bad data is the number one reason most AI projects fail.

Without a strategy, AI solutions risk never making it into production.

As stated before, the business must value data as a corporate asset. That is fundamental to your strategy. However, the thinking must go further. Any AI program must be tightly aligned to support the corporate strategy. Artificial intelligence is an enhanced capability to achieve your business goals.

Companies committed to adopting AI need to make sure their strategies are transformational and should make AI central to revising their corporate strategies.

(Report: MIT Sloan Management Review)

AI for AI’s sake often leads to long, drawn-out projects that never produce any real value. CEO support is the ideal. Executive sponsors are critical to ensure proper alignment, set business metrics for any technology implementation, and provide air cover against any disputes over data or technology involvement.

AI entrepreneur Jordan Jacobs lays out the three ingredients for a winning strategy:

Getting buy-in from the top executives and the employees who will use the system, identifying clearly the business problem to be solved, and setting metrics to demonstrate the technology’s return on investment.

(Jordan Jacobs)

According to MIT Technology Review, there are key questions a business must answer to formulate their strategy:

What is the problem the business is trying to solve? Is this problem amenable to AI and machine learning?

How will the AI solve the problem? How has the business problem been reframed into a machine-learning problem? What data will be needed to input into the algorithms?

Where does the company source its data? How is the data labeled?

How often does the company validate, test and audit its algorithms for accuracy and bias?

Is AI, or machine learning, the best and only way to solve this problem? Do the benefits outweigh potential privacy violations and other negative impacts?

Without cloud-based technologies, many AI solutions can’t operate.

For most businesses, embracing cloud-based computing and storage technologies are critical for AI programs to produce effectively. Artificial intelligence models require tremendous compute power to process massive data sets. This requires businesses to have ready access to computer power on-demand.

Since 2012, the amount of computation used in the largest AI training runs has been increasing exponentially with a 3.5 month doubling time (by comparison, Moore’s Law had an 18 month doubling period).

(OpenAI)

If AI programs are to be successful, companies need to embrace cloud technologies. They need to be willing to adopt platforms that provision GPU clusters based on workloads required by deployed models. Cloud is important because owning the hardware can cost over a million dollars for a single cluster, according to OpenAI.

Without internal expertise, AI adoption is challenging.

To successfully move AI projects through the development life-cycles, from data to production, you need to have in-house technical expertise. At minimum, you need to have dedicated data managers who can help wrangle data to train models. It is important to have software engineers or DevOps leads who can help move trained models into production environments so non-technical stakeholders can easily run reports. These two roles can be augmented by services providers that build and train models. However, it is better if you have data scientists, analysts, and data engineers who can help strategize and execute projects as well.

Without well-defined technology processes, projects risk never making it into production.

Another common risk associated with AI projects is that trained models don’t transition into production. It is important to have a connection between the business strategy and the delivery of AI technology. It’s especially important to have a plan in place for how to access the data, train the model, and handoff the model to be deployed as a usable solution.

Develop an operating model that defines AI roles and responsibilities for the business, technology teams, external vendors, and existing BPM centers of excellence. Some firms will separate model development — i.e., selecting and developing the AI, data science, and algorithms — from implementation. But over time, tech management will own deployment and operational management.

(Report: Forrester)

Moving forward it will be important to have documented processes for post-deployment. Once multiple models are in production you need to monitor models for performance and have a documented process for re-training.

Take an AI readiness assessment.

Many companies are not fully equipped to realize the full benefits created by artificial intelligence. And it is hard to know if “good enough” is good enough. Start by evaluating how equipped your business may be to successfully deploy projects. There are many ways to assess your readiness and de-risk investment. Online AI readiness assessments will help you start to understand if your organization has the prerequisites to successfully execute initial projects. If you are not ready, there is a lot of opportunity at stake. The most valuable thing you can do is to start to get ready. If you have executive buy-in, partner with consultancies or hire an AI strategist who can help put the pieces in place.

Originally Posted on KUNGFU.AI

from Gigaom https://gigaom.com/2019/06/18/why-many-businesses-are-not-ready-for-ai/

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Tech founders are giving millions to AI research so it doesn’t turn on us

No Terminator-like scenarios, please.

Image: GETTY IMAGES/ISTOCKPHOTO

Worried about a dystopian future in which AI rule the world and humans are enslaved to autonomous technology? You’re not alone. So are billionaires (kind of).

First it was the Partnership on AI formed by Google, Amazon, Microsoft, Facebook and IBM.

Then came Elon Musk and Peter Thiel’s recent investment in $1 billion research body, OpenAI.

Now, a new batch of tech founders are throwing money at ethical artificial intelligence (AI) and autonomous systems (AS). And experts say it couldn’t come sooner.

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LinkedIn founder, Reid Hoffman, and eBay founder, Pierre Omidyar (through his philanthropic investment fund) donated a combined $20 million to the Ethics and Governance of Artificial Intelligence Fund on Jan. 11 helping ensure the future’s more “man and machine, not man versus machine,” as IBM CEO Ginny Rometty put it to WSJ Thursday.

But how will they put their praxis where their prose is, and what’s at stake if they dont?

“There’s an urgency to ensure that AI benefits society and minimises harm,” said Hoffman in a statement distributed via fellow fund contributors, The Knight Foundation. “AI decision-making can influence many aspects of our world education, transportation, healthcare, criminal justice and the economy yet data and code behind those decisions can be largely invisible.”

That’s a sentiment echoed by Raja Chatila, executive committee chair for the IEEE Global Initiative for Ethical Considerations in Artificial Intelligence and Autonomous Systems.The IEEE Standards Association aims educate and empower technologists in the prioritisation of ethical considerations that, in their opinion, will make or break our relationship with AI and AS.

The organisation’s Ethically Aligned Design study, published in Dec., is step one in what they hope will be the beginning of a smarter working relationship between humans and systems.

“You either prioritise well-being or you don’t it’s a binary choice,” said Chatila.

Like Hoffman, Chatila feels a palpable sense of urgency when it comes to work of these research bodies. For him, our sense of democracy could be sacrificed if we begin fearing algorithms or data usage that we don’t fully understand, could distort our voice.

“The United Nations has chosen to prioritise the analysis and adoption of autonomous weapons in 2017.This is because beyond typical military issues, these discussions will very likely set precedents for every vertical in AI,” he told Mashable.

“Beyond the issue of weapons, what’s also really at stake is human agency as we know it today.When individuals have no control over how their data is used, especially in the virtual and augmented reality environment to come, we risk having outlets to express our subjective truth.” The algorithmic nightmare that was Facebook’s “fake news” comes to mind.

Meanwhile the Ethics and Governance of Artificial Intelligence Fund says it will aim to support a “cross-section of AI ethics and governance projects and activities,” globally and other members mentioned to date include Raptor Group founder Jim Pallotta and William and Flora Hewlett Foundation, who’ve committed another $1 million each.

Activities the fund will support, according to the statement, include a joint AI fellowship for people helping keep human interests at the forefront of their work, cross-institutional convening, research funding and promoting topics like ethical design, accountability, innovation and communicating about AI and AS more broadly.

Prioritising wellbeing from the get-go

While stewardship of ethical research in AI seems more urgent than ever, there’s no concrete cause for concern when it comes to innovation in the field. According to Chatila, current or future unintended ethical consequences aren’t the result of AI designers or companies being “evil” or uncaring.

“It’s just that you can’t build something that’s going to directly interact with humans and their emotions, that makes choices surrounding intimate aspects of their lives, and not qualify the actions a machine or system will take beforehand,” he said.

“For instance, if you build a phone with no privacy settings that captures people’s data, some users won’t care if they don’t mind sharing their data in a typical fashion.

“But for someone who doesn’t want to share their data in this way, they’ll buy a phone that honours their choices with settings that do so.This is why a lot of people are saying consumers will ‘pay for privacy.'” Which of course, becomes less of an issue if manufacturers are “building for values” from the get-go.

“We need to move beyond fear regarding AI, at least in terms of Terminator-like scenarios.This is where applied ethics, or due diligence around asking tough questions regarding the implementation of specific technologies, will best help end users, he said.

IEEE is currently working on a Standard along the lines of a “best practice” document called “P7000” that Chatila says will help update the systems development process to include explicitly Ethical factors.

Having organisations and companies become signatories [to industry standards] would be fantastic, where they reorient their innovation practices to include ethical alignment in this way from the start,” he said.

With OpenAI, the IEEEs Ethically Aligned Design project and now the Ethics and Governance of Artificial Intelligence Fund, there could be every chance companies will move beyond good intentions and into standardised practices that factor human well-being into design.

So long as they hurry the heck up. Innovation waits for nought.

“You either prioritise well-being or you don’t it’s a binary choice,” said Chatila. “And if you prioritise exponential growth, for instance, that means you can’t focus on a holistic picture that best reflects all of society’s needs.”

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