SEO (Search Engine Optimization) is a billion-dollar business. It will grow at a CAGR of 17.6% to reach <a href="https://www.acumenresearchandconsulting.com/search-engine-optimization-services-market">USD 234.8 Billion </a>by 2030 from USD 46.7 Billion in 2021. But probably not the way you think because AEO (Answer Engine Optimization) is here. Read the entire article for free <a href="https://open.substack.com/pub/trajectorymatrix/p/from-seo-to-aeo?utm_source=share&utm_medium=android&r=3590yk">here</a>.

As chatbots, smart assistants, and voice search gain popularity, users prefer getting quick answers without visiting a website. This type of search strategy is AEO.

Zero-Click Searches: Generative AI and Avoice search mean users seek direct answers.Voice Search and Conversational Queries: AEO will help content match more natural, longer voice queries. AI-Driven Content Optimization: As AI becomes more integrated into search engine algorithms, new optimization techniques will emerge. Large Language Model Optimization (LLMO): The optimization of large language models (LLMs) involves influencing their learning and training data to ensure a brand’s content is presented as an answer when relevant.

The Future of SEO and AEO

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Marketing & Sales

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Money & Investments

technologyandthefuture

Technology & The Future

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Strategy

business

Business

From SEO to AEO

THE 5 PILLARS OF SOCIAL MEDIA MARKETING

<ul><li class="ql-align-justify">Know who is your audiance is and which social platform they use</li><li class="ql-align-justify">Understand your goals</li><li class="ql-align-justify">Create effective, relavent content</li></ul>Posting the right content in the right places can save both time and money.E.g. If you want to build community around your brand, you might focus on interactive content like polls or question and answer sessions. But if your goal is to promote a new product, running a contest and giveaway might get better results.

<ul><li class="ql-align-justify">Ensures consistent presence</li><li class="ql-align-justify">Scheduling (When to post content)</li><li class="ql-align-justify">Timing & Frequency (How often to post content)</li></ul>The goal is to engage followers enough so that they remember you, but not so often that you overwhelm them.Social media scheduling tools can help you publish your content automatically at your preferred times.

Planning & Publishing

Social listening - Track and anayze social conversations and mentions related to your brand.Engagement- how your audience interacts with your brand on social media. WHY ?<ul><li class="ql-align-justify">Understand what people think about brand</li><li class="ql-align-justify">Inform marketing decision</li><li class="ql-align-justify">Learn what content resonates best with audience</li><li class="ql-align-justify">Increase people's positive experience with your brand</li></ul> Eg. If someone posts about how helpful they find a particular tool, like a habit tracking app, the brand could respond with thanks and encouragement. But if they post that the app isn't working correctly, they could share troubleshooting tips instead.

Social Listening & Engagement

Social media analytics is a process of collecting data from your social media platforms and analyzing that data to make business decisions. <ul><li class="ql-align-justify">Tell you how your campaign is performing.</li><li class="ql-align-justify">Drive social media marketing strategy</li><li class="ql-align-justify">Share social media reports with stakeholders</li></ul>A social media report is a document that presents relevant data and analysis about your social media activities.Setting up different reports on social media platforms allows you to monitor metrics like followers, comments, and clicks. This helps improve campaign performance over time with insights from built-in analytics tools.

Analytics & Reporting

<ul><li class="ql-align-justify">Control and target your marketing</li><li class="ql-align-justify">Reach a wider audience</li><li class="ql-align-justify">Grow your brand on social media</li><li class="ql-align-justify">Re-market products</li><li class="ql-align-justify">Serve ads to highly specific customer groups</li></ul> Social media ads targets to highly specific customer groups than than search engines.By linking ads to email sign-up forms, business can contact their followers directly and send them special offers.

Paid Social Media

Social media marketing is the practice of creating and publishing content for social media platforms in order to drive engagement and promote a brand or product.

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Startups

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Artificial Intelligence

5 Pillars of Social Media Marketing

In healthcare, AI’s impact has been very noticeable and deals with how diseases are detected, diagnosed, and treated. One of the first applications of AI in healthcare is IBM’s Watson, which got a lot of recognition for its ability to analyse large amounts of medical data to assist in diagnosing diseases.

Initial impact in healthcare

Machine Learning algorithms analyse medical imaging data such as X-rays and MRIs with high accuracy which helps in the early identification of diseases such as cancer. For example, Google’s AI system demonstrated the ability to detect breast cancer from mammograms with greater accuracy than human radiologists.

Detection

AI tool Mia, piloted by NHS, identified subtle signs of breast cancer in 11 women missed by human doctors out of 10,000 mammograms analyzed. With its early detection capabilities, Mia has the potential to save countless lives, highlighting the critical role of AI in improving breast cancer survival rates.

Google scientists developed HeAR, a machine-learning tool that can detect and monitor health conditions by analysing sounds like cough and breathing. Trained on millions of human audio clips, HeAR has potential for diagnosing diseases such as COVID-19 and tuberculosis, and assessing lung function. Unique to HeAR is its vast dataset and ability to perform various tasks.

AI-powered diagnostic tools analyze patient data to identify patterns and anomalies, helping clinicians in making more informed decisions. IBM’s Watson, for instance, assists oncologists in diagnosing and treating cancer by analyzing extensive patient data, leading to more personalized and effective treatment plans.

Diagnosis

AI is reshaping treatment methods with personalized medicine, where therapies are recommended to individual patients based on genetic and molecular profiles. AI algorithms predict optimal treatment for cancer patients, maximizing efficacy and minimizing side effects.

Treatment

AI-powered chatbots provide personalized healthcare recommendations, answer patient queries, and streamline administrative tasks. Predictive analytics algorithms have been used to forecast disease outbreaks, optimize hospital resource allocation, and improve patient care management.AI-driven robotic systems in the future will enhance surgical procedures, offering greater precision, efficiency, and safety.

Other areas

As AI continues to evolve, it will continue to drive innovation across the healthcare ecosystem in the way how diseases are detected, diagnosed, and treated. By leveraging the power of AI-driven technologies and collaboration among stakeholders, we can unlock new opportunities to enhance patient care, improve healthcare outcomes, and shape a healthier future for all.

In healthcare, AI’s impact has been very noticeable that deals with how diseases are detected, diagnosed, and treated. One of the first applications of AI in healthcare is IBM’s Watson, which got a…

health

Health

Recent AI advancements in healthcare

Want to instantly unlock the key ideas of a book? Just scan it with your camera.Here's the magic:<ol><li class="ql-align-justify">Open the Deepstash search screen and tap the scanner button (top right).</li><li class="ql-align-justify">Grant Deepstash camera access (if you haven't already).</li><li class="ql-align-justify">Point your camera at any book cover, making sure it fits the rectangle on your screen.</li><li class="ql-align-justify">Boom! Get ready to dive into the most popular ideas from the book.</li></ol>No more lugging around heavy tomes! Deepstash makes exploring books a breeze.P.S. Make sure the cover is clear and well-lit for the best results.

Turn your camera into a book scanner

This functionality enables some pretty cool use cases you could try:<ul><li class="ql-align-justify">Bookstore bonanza: Stumbled upon an intriguing cover but can't decide? Scan it to get a quick peek at the book's key ideas.</li><li class="ql-align-justify">Friend's bookshelf brag: Spark a conversation by scanning your friend's bookshelf and discussing the coolest finds.</li><li class="ql-align-justify">Web wanderer: Spot a captivating cover on Amazon? Scan it with Deepstash to see what the buzz is about.</li><li class="ql-align-justify">Social media detective: See a book your favorite influencer is raving about? Scan the cover to discover what all the hype is about.</li></ul>PS: All your scanned books will be collected in stash.

Use-cases to try

"I propose a new university curriculum: 'Literature by Gist.' Simply scan the cover art, and - bam! - you've got the gist. Saves a tremendous amount of time for pondering semicolons and all that rot. Though, I fear 'Moby Dick' might just translate to 'Angry Whale."

We have a magical new feature we can't wait for you to try.

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Productivity

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Learning & Education

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Books

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Product & Design

Mar '24 Update - Magic Book Scan

Deepfakes are hyper-realistic digital forgeries of human created using Generative AI.They use the deep learning principles in the backend to learn from human expressions and voice to later imitate them to do what they have never done.

What are Deep Fakes ?

<ul><li class="ql-align-justify">In entertainment industry, deep fakes can be used to create amazing visual effects and also bring back legendary actors who passed away.</li><li class="ql-align-justify">Artists and creators leverage deep fakes to try new content to play around with famous people in past to create an impact in art, education </li><li class="ql-align-justify">Personalised marketing is done by engaging consumers by featuring familiar faces in advertising content.</li></ul>

Positive Impacts

A short film explores deep fake technology with James Bond 007 Deepfake generated videos of historians in museum keep visitor engaged and excited

<ul><li class="ql-align-justify">Political figures deep fakes are used to spread fake news and misinformation which is a serious threat to democracy </li><li class="ql-align-justify">Deep fakes created without people‘s concern lead to privacy violations </li><li class="ql-align-justify">They actively contribute to fraud by impersonating people in video calls and getting funds. </li></ul>

Negative impact

Trump supporters targeted black voters with faked AI images. Italy‘s PM images are used to created compromising deep fake videos of her

Manual detection: one can detect visual deep fakes easily by observing features - inconsistent lighting or unnatural blinkingUsing technology: AI can be used to detect deep fakes and there are good amount of companies in this space. Blockchain can also be used to digital authenticateAwareness campaigns can empower individuals to critically evaluate the digital content they consume.

How to fight deepfakes ?

The dual nature of deepfake technology poses a significant challenge: it can either benefit society or fuel nefarious agendas. Effective management requires responsible use, strong legal frameworks, and advanced detection method

Conclusion

Explore about deepfakes - a double edged sword

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Cybersecurity

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Computer Science

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Software Engineering

The dual face of deepfakes - Innovation and Illusion

Explore how Liu Cixin's "dark forest" theory parallels the evolving landscape of the internet, transformed by generative AI. Delve into the challenges of maintaining authentic human interaction amidst the influx of bots, scammers, and synthetic content. This piece aims to shed light on the complexities of digital communication in an age where distinguishing between real and artificial becomes increasingly difficult.

The Dark Forest Theory and the Internet: Navigating the New Digital Wilderness

This video examines the impact of generative artificial intelligence, including large language models and tools capable of creating lifelike text, images, and videos. Discuss the growing difficulty in discerning real from synthetic online and the implications for trust and authenticity in digital spaces.

The Rise of AI and the Challenge of Authenticity Online

Investigate the concept of the "Reverse Turing Test," where the onus falls on humans to demonstrate their humanity within a digital realm proliferated by AI entities. This discussion includes practical strategies for asserting human presence online, emphasizing the importance of human signals in an AI-saturated environment

Proving Humanity: The Reverse Turing Test in a World Dominated by AI

Focus on Kyle Hill's proposed methods for humans to signal their authenticity in a digital world crowded with AI-generated content. From physical presence to institutional verification and the pursuit of algorithmic incoherence, explore how individuals and communities can maintain genuine human connections and interactions online.

Strategies for Human Signaling in the Age of Generative AI

Balance the optimistic potential of generative AI in revolutionizing education and medical research with the darker possibilities of deepfakes and scams. Highlight the need for a nuanced understanding and approach to generative AI, acknowledging its capacity to both significantly benefit and challenge society

The Double-Edged Sword of Generative AI: Potential Perils and Promises

New generative A.I breakthroughs are happening almost every week, it seems. The big question is; Are we ready for it? Noted Science Zaddy Kyle Hill explains what’s coming, the “dark forest” theory of the internet, and the steps we humans can take to pass the “Reverse Turing Test.”

Watch Maggie Appleton’s talk here: https://youtu.be/VXkDaDDJjoA 

00:00 Intro
01:49 The Expanding Forest 
06:08 The Reverse Turing Test
10:28 Algorithmically Incoherent 
14:05 A Warning.

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Science Fiction

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Videos

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Science & Nature

Award-winning science educator. White House sci-comm advisor. Clean Future Fund's Dogs of Chernobyl ambassador. “A sexy vampire…a legend.” - Post Malone

Kyle Hill
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Kyle Hill

Generative A.I - We Aren’t Ready.

Have you ever wondered how much of the universe we actually know? Surprisingly, it's only 20%! 🤯 There is still so much more to discover. 🚀


With all the advancements in science, we are only scratching the surface of the secrets the universe holds. 🔭 Let's keep exploring and unraveling its mysteries. 🔍

The Mystery of the Universe 🌌

Deep in the vastness of space, dark matter conducts a cosmic dance, influencing the essence of our universe. Despite its unseen nature, its undeniable presence shapes the fabric of our universe.
Key Concepts:
<ul>
	<li>Silent depths of space</li>
	<li>Dark matter</li>
	<li>Cosmic ballet</li>
	<li>Enigmatic presence</li>
	<li>Fabric of the universe</li>
</ul>

The Enigma of Dark Matter

Explore the cosmic whispers of dark matter, an ethereal presence that enchants and entices us with its cosmic symphony and secrets. 
 Marvel at the melodies that dance through galaxies, beckoning us to ponder the mysteries of the cosmos and the unknown.

The Mysteries of Dark Matter

"Dark matter may shroud itself in mystery, but its gravitational embrace reveals a cosmic dance beyond our perception, weaving the unseen threads of the universe's tapestry."

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Creativity

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Space

Dark matter: a reservoir of unknown

Artificial Intelligence (AI) has become an integral part of our daily lives, influencing decisions from personalised recommendations to critical healthcare diagnostics. Now with the ChatGPT, LLMs and other Generative AI technologies being emerging at a jet speed, there are some critical grey areas which demand our attention, with ethical considerations taking center stage. This article discusses about six key pillars of AI ethics

Accountability means making sure someone is responsible for the actions and outcomes of AI systems. It’s about being ready to fix mistakes and improve the system when needed.Example - Self-driving vehicles: For AI-driven cars, if there’s an accident, figuring out if the car's programming, the manufacturer, or something else is at fault is key to accountability.

Accountability

Fairness in AI ensures that AI systems treat everyone equally, without bias against any gender, race, or ethnicity. It aims to prevent discrimination and promote equality.Example - Application Tracking Systems (ATS): If an ATS used in hiring favors certain demographics because of its training data, it's crucial to address this bias. Ensuring fairness in such AI models helps create a more inclusive society.

Fairness:

Explainability is about making AI's decision-making transparent, so users can understand and trust how it reaches its conclusions.Example - AI in Finance: For an AI deciding on loan approvals, explainability means it can show which factors influenced its decision, helping applicants understand or contest the outcome.

Explainability

Transparency means openly sharing how AI systems work, from data use to decision-making processes, fostering trust and informed user interaction.Example - AI in Social Media: When social media platforms explain how their algorithms tailor user feeds, they promote transparency, empowering users to better control their online experience.

Transparency

Robustness is about making AI reliable in unforeseen conditions, ensuring it performs well even when faced with challenges like data changes or attacks.Example - Facial Recognition: A robust facial recognition system accurately identifies users under various conditions, like changes in lighting or expression, minimising errors and boosting dependability.

Robustness

Privacy focuses on protecting personal data from misuse or unauthorized access, emphasizing the responsible management of sensitive information.Example - Fitbit watches: Privacy in devices like Fitbit ensures users' health data is securely stored and accessed responsibly, fostering trust in how their information is handled.

Privacy

Adhering to the six pillars of AI ethics — Accountability, Fairness, Explainability, Transparency, Robustness, and Privacy — ensures AI systems are developed responsibly. These principles guide organizations in using AI while safeguarding users' rights and safety. Committing to these values fosters a trustworthy, ethical AI environment for all.

Explore pillars of Trustworthy and Responsible AI

Artificial Intelligence (AI) has become an integral part of our daily lives, influencing decisions from personalised recommendations to critical healthcare diagnostics. Now with the ChatGPT, LLMs and…

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Human Resources

Ethical foundations of AI

The world of AI is evolving rapidly, and one of the hottest trends in 2024 is Edge AI. This technology that revolutionises the way we interact with machines and make decisions using the power of on-device intelligence.Imagine a world where your smart speaker understands your voice instantly, your self-driving car reacts to obstacles in real-time, and your medical device makes critical decisions without waiting for cloud approval. This is the power of Edge AI.

What is Edge AI?

By 2025, over half of all data analysis performed by deep learning algorithms will occur directly on edge devices, a significant jump from just 10% in 2021.

Edge AI performs calculations directly on the device itself in real-time where the data is created which creates <ul><li class="ql-align-justify">Faster response times: No more waiting for data to travel back and forth, reducing the ‘cloud lag’ leading to immediate and accurate decisions. This is really important for applications like autonomous vehicles and critical healthcare devices.</li><li class="ql-align-justify">Enhanced privacy and security: Sensitive data is localised that reduces the risk of external threats. Edge AI can be beneficial for protecting sensitive medical information or financial transactions.</li></ul>

Advantages:

This rapid growth is driven by several factors:<ul><li class="ql-align-justify">Advancements in chip technology: More powerful and energy-efficient processors are making it possible to run complex AI algorithms on smaller devices.</li><li class="ql-align-justify">Growth of the Internet of Things (IoT): The connected devices, from smart homes to industrial sensors, generates vast amounts of data that can be analysed locally.</li><li class="ql-align-justify">Increasing demand for real-time decision-making: Applications like autonomous vehicles and smart factories require instant responsiveness</li></ul>

Drivers of Edge AI

Healthcare: Wearable devices can analyse health data in real-time, enabling early detection of diseases and personalised treatment plans.Manufacturing: Smart factories can optimize production processes, predict equipment failures, and improve overall efficiency.Retail: Personalised recommendations and targeted advertising based on real-time customer behavior can be delivered in stores.Smart homes: Devices like smart speakers and thermostats can learn individual preferences and adjust automatically, creating a more comfortable and energy-efficient living environment.

The future of Edge AI and applications

<ul><li class="ql-align-center">Securing edge devices and protecting sensitive data processed on them is important.</li><li class="ql-align-center">Balancing the benefits of personalised experiences with user privacy requires careful consideration.</li><li class="ql-align-center">Not all devices have the processing power to run complex AI models. Finding efficient algorithms and hardware solutions will be key.</li></ul>

Edge AI is not just a trend; it’s a paradigm shift in how we interact with intelligent systems. As technology continues to advance, Edge AI promises to bring faster, more responsive, and secure AI capabilities to every aspect of our lives, shaping a future where intelligence is truly distributed and embedded in every fabric of our world.

Learn about Edge AI for faster, more responsive decisions

The world of AI is evolving rapidly, and one of the hottest trends in 2024 is Edge AI. This technology that revolutionises the way we interact with machines and make decisions using the power of…

The rise of on-device intelligence 

AI, or Artificial Intelligence, refers to the simulation of human intelligence in machines, enabling them to perform tasks that typically require human intelligence, such as learning, reasoning, and problem-solving.

What is Artificial Intelligence

Predictive AI analyzes existing data to make predictions or decisions, while Generative AI creates new data instances, such as images or text. Predictive AI predicts future outcomes based on historical data, while Generative AI generates new content, like images or music, based on learned patterns.

Type: Predictive AI vs Generative AI

Predictive AI examples include recommendation systems (like those used by Netflix or Amazon), fraud detection algorithms in banking, and predictive maintenance in manufacturing.

Predictive AI examples

Generative AI examples in use include ChatGPT, Gemini like tools that help in creating text and DALL-E and Sora by OpenAI, which creates images and videos from textual descriptions respectively.

Generative AI examples

Machine Learning, Deep learning, Natural Language Processing, Computer Vision

Fields of AI

Machine learning is a subset of AI that enables computers to learn from data without being explicitly programmed. It involves algorithms that improve automatically through experience, allowing computers to recognize patterns and make decisions without human intervention.

Machine Learning

Deep learning is a subfield of machine learning that uses artificial neural networks with multiple layers to learn representations of data. It's particularly effective for tasks like image and speech recognition, where large amounts of data are available

Deep Learning

Natural language processing (NLP) enables computers to understand, interpret, and generate human language. It's used in applications like language translation, sentiment analysis, and chatbots to analyze and generate text-based data.

Natural language processing

Computer vision enables computers to interpret and understand visual information from images or videos. It's used in applications like facial recognition, object detection, and autonomous vehicles to process and analyze visual data.

Computer Vision

"AI won't replace you rather it will empower you. Embrace its potential to augment your capabilities, streamline tasks, and unlock new opportunities for creativity and innovation."

Challenges in AI today include bias in algorithms, data privacy concerns, and the ethical implications of AI technologies. Additionally, the complexity and resource-intensive nature of AI algorithms pose challenges for implementation and scalability.

Challenges in AI

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Entrepreneurship

AI for everyone

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