#analytical bias

[chocolatepot]

I'm feeling really cranky tonight and I don't know why. Like yes the things I'm being cranky about are making me cranky but usually they don't annoy me so much?

[zvaigzdelasas]

An AI that tries to predict code implementations from a tree of type/interface definitions would likely be a very fruitful avenue for development

[inavagrant-a]

I love how Wanderer’s Korean VA always sounds like he’s pissed off about something as he should, awraxa.

[jcmarchi]

Future-Ready Enterprises: The Crucial Role of Large Vision Models (LVMs)

New Post has been published on https://thedigitalinsider.com/future-ready-enterprises-the-crucial-role-of-large-vision-models-lvms/

Future-Ready Enterprises: The Crucial Role of Large Vision Models (LVMs)

What are Large Vision Models (LVMs)

Over the last few decades, the field of Artificial Intelligence (AI) has experienced rapid growth, resulting in significant changes to various aspects of human society and business operations. AI has proven to be useful in task automation and process optimization, as well as in promoting creativity and innovation. However, as data complexity and diversity continue to increase, there is a growing need for more advanced AI models that can comprehend and handle these challenges effectively. This is where the emergence of Large Vision Models (LVMs) becomes crucial.

LVMs are a new category of AI models specifically designed for analyzing and interpreting visual information, such as images and videos, on a large scale, with impressive accuracy. Unlike traditional computer vision models that rely on manual feature crafting, LVMs leverage deep learning techniques, utilizing extensive datasets to generate authentic and diverse outputs. An outstanding feature of LVMs is their ability to seamlessly integrate visual information with other modalities, such as natural language and audio, enabling a comprehensive understanding and generation of multimodal outputs.

LVMs are defined by their key attributes and capabilities, including their proficiency in advanced image and video processing tasks related to natural language and visual information. This includes tasks like generating captions, descriptions, stories, code, and more. LVMs also exhibit multimodal learning by effectively processing information from various sources, such as text, images, videos, and audio, resulting in outputs across different modalities.

Additionally, LVMs possess adaptability through transfer learning, meaning they can apply knowledge gained from one domain or task to another, with the capability to adapt to new data or scenarios through minimal fine-tuning. Moreover, their real-time decision-making capabilities empower rapid and adaptive responses, supporting interactive applications in gaming, education, and entertainment.

How LVMs Can Boost Enterprise Performance and Innovation?

Adopting LVMs can provide enterprises with powerful and promising technology to navigate the evolving AI discipline, making them more future-ready and competitive. LVMs have the potential to enhance productivity, efficiency, and innovation across various domains and applications. However, it is important to consider the ethical, security, and integration challenges associated with LVMs, which require responsible and careful management.

Moreover, LVMs enable insightful analytics by extracting and synthesizing information from diverse visual data sources, including images, videos, and text. Their capability to generate realistic outputs, such as captions, descriptions, stories, and code based on visual inputs, empowers enterprises to make informed decisions and optimize strategies. The creative potential of LVMs emerges in their ability to develop new business models and opportunities, particularly those using visual data and multimodal capabilities.

Prominent examples of enterprises adopting LVMs for these advantages include Landing AI, a computer vision cloud platform addressing diverse computer vision challenges, and Snowflake, a cloud data platform facilitating LVM deployment through Snowpark Container Services. Additionally, OpenAI, contributes to LVM development with models like GPT-4, CLIP, DALL-E, and OpenAI Codex, capable of handling various tasks involving natural language and visual information.

In the post-pandemic landscape, LVMs offer additional benefits by assisting enterprises in adapting to remote work, online shopping trends, and digital transformation. Whether enabling remote collaboration, enhancing online marketing and sales through personalized recommendations, or contributing to digital health and wellness via telemedicine, LVMs emerge as powerful tools.

Challenges and Considerations for Enterprises in LVM Adoption

While the promises of LVMs are extensive, their adoption is not without challenges and considerations. Ethical implications are significant, covering issues related to bias, transparency, and accountability. Instances of bias in data or outputs can lead to unfair or inaccurate representations, potentially undermining the trust and fairness associated with LVMs. Thus, ensuring transparency in how LVMs operate and the accountability of developers and users for their consequences becomes essential.

Security concerns add another layer of complexity, requiring the protection of sensitive data processed by LVMs and precautions against adversarial attacks. Sensitive information, ranging from health records to financial transactions, demands robust security measures to preserve privacy, integrity, and reliability.

Integration and scalability hurdles pose additional challenges, especially for large enterprises. Ensuring compatibility with existing systems and processes becomes a crucial factor to consider. Enterprises need to explore tools and technologies that facilitate and optimize the integration of LVMs. Container services, cloud platforms, and specialized platforms for computer vision offer solutions to enhance the interoperability, performance, and accessibility of LVMs.

To tackle these challenges, enterprises must adopt best practices and frameworks for responsible LVM use. Prioritizing data quality, establishing governance policies, and complying with relevant regulations are important steps. These measures ensure the validity, consistency, and accountability of LVMs, enhancing their value, performance, and compliance within enterprise settings.

Future Trends and Possibilities for LVMs

With the adoption of digital transformation by enterprises, the domain of LVMs is poised for further evolution. Anticipated advancements in model architectures, training techniques, and application areas will drive LVMs to become more robust, efficient, and versatile. For example, self-supervised learning, which enables LVMs to learn from unlabeled data without human intervention, is expected to gain prominence.

Likewise, transformer models, renowned for their ability to process sequential data using attention mechanisms, are likely to contribute to state-of-the-art outcomes in various tasks. Similarly, Zero-shot learning, allowing LVMs to perform tasks they have not been explicitly trained on, is set to expand their capabilities even further.

Simultaneously, the scope of LVM application areas is expected to widen, encompassing new industries and domains. Medical imaging, in particular, holds promise as an avenue where LVMs could assist in the diagnosis, monitoring, and treatment of various diseases and conditions, including cancer, COVID-19, and Alzheimer’s.

In the e-commerce sector, LVMs are expected to enhance personalization, optimize pricing strategies, and increase conversion rates by analyzing and generating images and videos of products and customers. The entertainment industry also stands to benefit as LVMs contribute to the creation and distribution of captivating and immersive content across movies, games, and music.

To fully utilize the potential of these future trends, enterprises must focus on acquiring and developing the necessary skills and competencies for the adoption and implementation of LVMs. In addition to technical challenges, successfully integrating LVMs into enterprise workflows requires a clear strategic vision, a robust organizational culture, and a capable team. Key skills and competencies include data literacy, which encompasses the ability to understand, analyze, and communicate data.

The Bottom Line

In conclusion, LVMs are effective tools for enterprises, promising transformative impacts on productivity, efficiency, and innovation. Despite challenges, embracing best practices and advanced technologies can overcome hurdles. LVMs are envisioned not just as tools but as pivotal contributors to the next technological era, requiring a thoughtful approach. A practical adoption of LVMs ensures future readiness, acknowledging their evolving role for responsible integration into business processes.

[meltorights]

i mean yeah a thoughtful if somewhat confusing exploration of postcolonialism vs.... perhaps every person is TWO objects instead of one?! does make analytic look kinda silly.

i thought abt putting two papers where theyre talking abt the same subject (like gender or something) and i feel like analytic might fare a bit better there just bc it's more comprehensible. But the general tendency is for analytic to tackle small distinctions with sometimes absurd results (following strictly from Formal Logic) while continentals talk about Big Questions like being human and rights in a broader context and stuff you cant necessarily apply Formal Logic to so i wanted to show that.

[techtoio]

How Artificial Intelligence is Transforming Scientific Research

Introduction No one ever imagined how artificial intelligence would revolutionize scientific research. At TechtoIO, we look into how AI is not just a tool but the driver behind the rapid advancements in many scientific disciplines. That includes how science is being transformed—from better data analysis to catalyzing discovery, such as areas in health, climate science, physics, particle experimentation, and more. Read to continue link...

[garymdm]

The Road to Decision Nirvana: Why Data Still Reigns Supreme

We all strive for perfect decision-making. But let’s face it, flipping a coin isn’t always the answer. Decision Making vs Decision SupportThe Data Dilemma:The Takeaway: Decision Making vs Decision Support That’s where decision support systems (DSS) come in. These clever tools analyse data, run simulations, and offer insights, but they leave the final call to you. They’re the ultimate research…

[sweetlog]

When Science Becomes a Pawn in the Game of Agendas

Science is often seen as the beacon of truth and objectivity, a pure pursuit of knowledge for the betterment of humanity. But what happens when this noble quest is hijacked by those with ulterior motives?

Take a journey through history, and you’ll find numerous occasions where science was not just a tool for discovery but also a weapon wielded for political gain. From the tobacco industry’s infamous manipulation of health studies to the distortion of climate change data, the narrative of ‘scientific consensus’ has been strategically shaped and reshaped to fit the needs of the powerful.

It’s a tale as old as time: an organization funds a study, hoping the results will back their product or policy. When the science aligns with their interests, it’s paraded in front of the public and policymakers alike, a testament to the ‘rightness’ of their cause. But when the results are inconvenient, they’re dismissed, discredited, or worse, buried in the annals of forgotten research.

Tobacco Industry and Health Studies For decades, the tobacco industry funded research to cast doubt on the harmful effects of smoking. This campaign of misinformation aimed to delay regulatory and public health interventions. Notorious for manipulating scientific evidence, the industry created a narrative of uncertainty around smoking’s health risks, despite overwhelming evidence to the contrary.

Climate Change and Energy Corporations Energy corporations, particularly those in the fossil fuel sector, have been accused of promoting skepticism about climate change. Despite a consensus among climate scientists about the human impact on global warming, these companies have financed studies and campaigns to amplify uncertainty and hinder environmental regulation.

Political Agendas and Public Health In some cases, political entities have selectively used scientific data to push health-related policies. For example, during the COVID-19 pandemic, various governments and organizations were criticized for cherry-picking scientific findings to justify their approach to lockdowns, mask mandates, and vaccine rollouts, often ignoring the broader consensus or evolving nature of the science.

Biased Funding and Research Direction Politics can deeply influence the direction and quality of scientific research through funding agendas. When companies or political groups fund scientific studies, there is a risk that the research may be biased towards outcomes that support the funder’s products or policies.

The politicization of science is not just a betrayal of the scientific method; it’s a breach of public trust. It creates a world where facts are flexible, and truth is transactional. It’s a world where the question “What does the science say?” is less about empirical evidence and more about who’s funding the research.

So, what’s the takeaway? Be vigilant. Question the source. Understand the funding. And remember, true science doesn’t serve an agenda; it seeks to understand the world, irrespective of the implications.

[sophiaphile]

"I chose my words carefully and was heard at first in silence, then a widespread murmuring began that swelled into bursts of laughter. Next day an acquaintance told me, 'I'm sorry we laughed McCandless, but to hear you steadily quoting Comte and Huxley and Haeckel in your broad Border dialect was like hearing the Queen opening Parliament in the voice of a Cockney costermonger.'

While speaking I did not know what so greatly amused folk . . . As I reached the door a piercing sound brought me to a stop and struck silence into everyone else. Godwin Baxter was speaking from the gallery. In a shrill drawl . . . he demonstrated how each of the platform speakers had used arguments that undermined all they aimed to prove. He ended by saying '—And those on the platform are the chosen few! The response to the last speaker's sensible argument shows the mental quality of the mass.'

I said, 'Thank you, Baxter,' and left."

—Alasdair Gray, Poor Things: Episodes from the Early Life of Archibald McCandless M.D., Scottish Public Health Officer

[themanjeet]

Ethical Considerations in Data Analytics: Privacy, Bias, and Responsible Use

Data analytics is a powerful tool that can be used to improve decision-making and solve complex problems.

https://medium.com/@rolandmack63/ethical-considerations-in-data-analytics-privacy-bias-and-responsible-use-36fd9461df5d

[mtbcleadgenbuzz]

Why Local Businesses Are Turning To AI For Content Creation: The Benefits Of Custom, Data-Driven Marketing!

Why Local Businesses Are Turning To AI For Content Creation: The Benefits Of Custom, Data-Driven Marketing! Local businesses are turning to AI for content creation more than ever before. With the rise of digital marketing, companies are realizing that traditional advertising methods may no longer be enough to stay competitive in today’s fast-paced world. The benefits of custom, data-driven…

[needtricks-blog]

From Mythology to Reality: Exploring the Past, Present, and Future of AI

Artificial Intelligence (AI) has rapidly become a ubiquitous part of our lives, from voice assistants and image recognition to self-driving cars and personalized advertising. While the technology continues to advance, there is still much debate and discussion around the implications and ethics of its use. (more…) “”

[jcmarchi]

Non-fiction books that explore AI's impact on society  - AI News

New Post has been published on https://thedigitalinsider.com/non-fiction-books-that-explore-ais-impact-on-society-ai-news/

Non-fiction books that explore AI's impact on society  - AI News

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Artificial Intelligence (AI) is code or technologies that perform complex calculations, an area that encompasses simulations, data processing and analytics.

AI has increasingly grown in importance, becoming a game changer in many industries, including healthcare, education and finance. The use of AI has been proven to double levels of effectiveness, efficiency and accuracy in many processes, and reduced cost in different market sectors. 

AI’s impact is being felt across the globe, so, it is important we understand the effects of AI on society and our daily lives. 

Better understanding of AI and all that it does and can mean can be gained from well-researched AI books.

Books on AI provide insights into the use and applications of AI. They describe the advancement of AI since its inception and how it has shaped society so far. In this article, we will be examining recommended best books on AI that focus on the societal implications.

For those who don’t have time to read entire books, book summary apps like Headway will be of help.

Book 1: “Superintelligence: Paths, Dangers, Strategies” by Nick Bostrom

Nick Bostrom is a Swedish philosopher with a background in computational neuroscience, logic and AI safety. 

In his book, Superintelligence, he talks about how AI  can surpass our current definitions of intelligence and the possibilities that might ensue.

Bostrom also talks about the possible risks to humanity if superintelligence is not managed properly, stating AI can easily become a threat to the entire human race if we exercise no control over the technology. 

Bostrom offers strategies that might curb existential risks, talks about how Al can be aligned with human values to reduce those risks and suggests teaching AI human values.

Superintelligence is recommended for anyone who is interested in knowing and understanding the implications of AI on humanity’s future.

Book 2: “AI Superpowers: China, Silicon Valley, and the New World Order” by Kai-Fu Lee

AI expert Kai-Fu Lee’s book, AI Superpowers: China, Silicon Valley, and the New World Order, examines the AI revolution and its impact so far, focusing on China and the USA. 

He concentrates on the competition between these two countries in AI and the various contributions to the advancement of the technology made by each. He highlights China’s advantage, thanks in part to its larger population. 

China’s significant investment so far in AI is discussed, and its chances of becoming a global leader in AI. Lee believes that cooperation between the countries will help shape the future of global power dynamics and therefore the economic development of the world.

In thes book, Lee states AI has the ability to transform economies by creating new job opportunities with massive impact on all sectors. 

If you are interested in knowing the geo-political and economic impacts of AI, this is one of the best books out there. 

Book 3: “Life 3.0: Being Human in the Age of Artificial Intelligence” by Max Tegmark

Max Tegmark’s Life 3.0 explores the concept of humans living in a world that is heavily influenced by AI. In the book, he talks about the concept of Life 3.0, a future where human existence and society will be shaped by AI. It focuses on many aspects of humanity including identity and creativity. 

Tegmark envisions a time where AI has the ability to reshape human existence. He also emphasises the need to follow ethical principles to ensure the safety and preservation of human life. 

Life 3.0 is a thought-provoking book that challenges readers to think deeply about the choices humanity may face as we progress into the AI era. 

It’s one of the best books to read if you are interested in the ethical and philosophical discussions surrounding AI.

Book 4: “The Fourth Industrial Revolution” by Klaus Schwab

Klaus Martin Schwab is a German economist, mechanical engineer and founder of the World Economic Forum (WEF). He argues that machines are becoming smarter with every advance in technology and supports his arguments with evidence from previous revolutions in thinking and industry.

He explains that the current age – the fourth industrial revolution – is building on the third: with far-reaching consequences.

He states use of AI in technological advancement is crucial and that cybernetics can be used by AIs to change and shape the technological advances coming down the line towards us all.

This book is perfect if you are interested in AI-driven advancements in the fields of digital and technological growth. With this book, the role AI will play in the next phases of technological advancement will be better understood.

Book 5: “Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy” by Cathy O’Neil

Cathy O’Neil’s book emphasises the harm that defective mathematical algorithms cause in judging human behaviour and character. The continual use of maths algorithms promotes harmful results and creates inequality.

An example given in  the book is of research that proved bias in voting choices caused by results from different search engines.

Similar examination is given to research that focused Facebook, where, by making newsfeeds appear on users’ timelines, political preferences could be affected.

This book is best suited for readers who want to adventure in the darker sides of AI that wouldn’t regularly be seen in mainstream news outlets.

Book 6: “The Age of Em: Work, Love, and Life when Robots Rule the Earth” by Robin Hanson

An associate professor of economics at George Mason University and a former researcher at the Future of Humanity Institute of Oxford University, Robin Hanson paints an imaginative picture of emulated human brains designed for robots. What if humans copied or “emulated” their brains and emotions and gave them to robots?

He argues that humans who become “Ems” (emulations) will become more dominant in the future workplace because of their higher productivity.

An intriguing book for fans of technology and those who love intelligent predictions of possible futures.

Book 7: “Architects of Intelligence: The truth about AI from the people building it” by Martin Ford

This book was drawn from interviews with AI experts and examines the struggles and possibilities of AI-driven industry.

If you want insights from people actively shaping the world, this book is right for you!

CONCLUSION

These books all have their unique perspectives but all point to one thing – the advantages of AI of today will have significant societal and technological impact. These books will give the reader glimpses into possible futures, with the effects of AI becoming more apparent over time.

For better insight into all aspects of AI, these books are the boosts you need to expand your knowledge. AI is advancing quickly, and these authors are some of the most respected in the field. Learn from the best with these choice reads.

[drthomasmaples]

Practical Psychology: How 2 Deal with the Negative Skew of News and Social Media

Practical Psychology: How 2 Deal with the Negative Skew of News and Social Media

A Sacred Journey Podcast Faith and Practical Psychology With so much media buying for our attention, how can we develop that desperately needed inner sense of peace? This is especially true as it relates to the negative bias most sources of information used to play upon the strengths of the autonomic nervous system that will shut down executive functioning when faced with either real or…

[techtoio]

Unlocking Insights: How Machine Learning Is Transforming Big Data

Introduction

Big data and machine learning are two of the most transformative technologies of our time. At TechtoIO, we delve into how machine learning is revolutionizing the way we analyze and utilize big data. From improving business processes to driving innovation, the combination of these technologies is unlocking new insights and opportunities. Read to continue

[garymdm]

Preconceived ideas lead to big data failures!

7 December 2014 is the 53rd anniversary of the Japanese attack on the US Naval base at Pearl Harbour that brought the United States into the Second World War. It is Sunday – just as it was 53 years ago. The attack saw the Japanese strike a significant blow against the US Pacific fleet sinking and severely damaging all 8 US battleships and a number of other vessels. Crucially, intelligence…