#internet of things data analytics

[primathontechnology]

IoT Data Analytics Benefits

Explore how IoT data analytics can transform industries. Learn about key use cases and the benefits of leveraging IoT for more intelligent business decisions and efficiency. In this context, Internet of Things data analytics relates to the collection, transformation, and analysis of data from Internet of Things devices.

[hanasatoblogs]

Big Data and the Internet of Things (IoT): The Power of Analytics

In today’s hyperconnected world, the intersection of the Internet of Things (IoT) and Big Data analytics is reshaping industries, providing businesses with unprecedented insights, and fueling a new wave of innovation. The vast amount of data generated by IoT devices offers immense opportunities to derive actionable insights. By leveraging IoT Big Data solutions, companies can optimize processes, enhance customer experiences, and drive business growth.

This article explores how IoT Big Data analytics, IoT Big Data architecture, and machine learning are transforming industries and providing valuable solutions.

The Explosion of IoT Data

The Internet of Things refers to the network of physical devices connected to the internet, gathering and sharing data. These devices include everything from smart home appliances and wearable health monitors to industrial sensors and autonomous vehicles. According to Statista, the number of IoT-connected devices is projected to reach 30.9 billion by 2025, generating a massive amount of data.

This data deluge presents significant challenges but also immense opportunities for organizations. By implementing IoT Big Data solutions, companies can collect, store, analyze, and act on this vast amount of information to improve decision-making, efficiency, and innovation.

IoT Big Data Analytics: Turning Data Into Insights

One of the most significant advantages of combining IoT with Big Data analytics is the ability to transform raw data into actionable insights. IoT Big Data analytics involves analyzing large volumes of data generated by IoT devices to identify patterns, trends, and anomalies that can inform business decisions.

Real-World Application: In the automotive industry, companies like Tesla use IoT sensors embedded in vehicles to monitor real-time data related to performance, maintenance needs, and driving patterns. This data is then processed through Big Data analytics to improve vehicle performance, anticipate maintenance issues, and even enhance autonomous driving features. Tesla’s ability to leverage IoT Big Data is a key factor in its innovative approach to automotive technology.

Moreover, GE Aviation uses IoT sensors in aircraft engines to monitor real-time performance data. By leveraging Big Data analytics, GE predicts engine failures and schedules proactive maintenance, improving safety and reducing downtime.

IoT Big Data Architecture: The Backbone of Data Processing

To efficiently process and analyze data from millions of IoT devices, businesses need a scalable and robust IoT Big Data architecture. This architecture typically includes:

Data Collection Layer: Sensors and devices collect and transmit data.

Data Ingestion Layer: Middleware solutions or platforms like Apache Kafka are used to ingest data in real-time, handling the large influx of information from various IoT sources.

Data Storage Layer: Data is stored in cloud-based or on-premise databases. Solutions like AWS IoT or Azure IoT are popular choices for storing and managing vast amounts of IoT data.

Data Processing and Analytics Layer: Advanced analytics platforms, such as Hadoop or Apache Spark, process large datasets to extract insights.

Visualization Layer: Insights are presented through dashboards or visualization tools, allowing stakeholders to make informed decisions.

This architecture supports the seamless flow of data from collection to actionable insights, enabling organizations to scale their IoT initiatives.

IoT and Machine Learning: Driving Smarter Solutions

The integration of machine learning with IoT Big Data creates smarter, more predictive systems. Machine learning models analyze the vast datasets generated by IoT devices to detect patterns, learn from them, and predict future outcomes. This combination unlocks powerful IoT Big Data solutions for industries ranging from healthcare to manufacturing.

Practical Example: In healthcare, IoT medical devices such as wearable fitness trackers and smart medical sensors monitor patients’ vitals, including heart rate, blood pressure, and oxygen levels. By feeding this data into machine learning models, healthcare providers can predict potential health risks and intervene early. For instance, machine learning algorithms can detect irregular heart patterns in real-time and alert doctors before a critical event occurs, ultimately saving lives.

In manufacturing, IoT sensors on equipment monitor real-time performance and detect potential failures. By integrating machine learning, manufacturers can predict when machinery is likely to fail and schedule maintenance ahead of time. This proactive approach reduces downtime and increases efficiency.

IoT Big Data Solutions: Real-World Impact

Industries are already reaping the benefits of IoT Big Data solutions, transforming how they operate and deliver value to customers.

Smart Cities: Cities like Barcelona and Singapore have deployed IoT sensors to monitor traffic patterns, optimize waste management, and manage energy consumption. With Big Data analytics, city administrators can improve urban planning and enhance the quality of life for residents. Smart traffic systems use IoT data to reduce congestion, while smart lighting systems adjust brightness based on real-time data to conserve energy.

Retail: IoT sensors in stores can monitor customer behavior, including how long they spend in certain areas or which products they interact with the most. Retailers like Amazon leverage this data to personalize in-store experiences, manage inventory more efficiently, and optimize store layouts. Amazon Go stores, for example, use IoT sensors to track what customers pick up, allowing for a seamless checkout-free shopping experience.

Agriculture: IoT devices in agriculture monitor soil conditions, weather patterns, and crop health. IoT Big Data analytics helps farmers optimize water usage, improve crop yields, and reduce waste. Companies like John Deere use IoT data from smart farming equipment to provide farmers with real-time insights on field conditions, enabling more precise and efficient farming practices.

Overcoming IoT Big Data Challenges

While the potential of IoT Big Data is vast, there are challenges that businesses need to overcome to fully realize its value.

Data Security: With the large volume of sensitive data being collected, organizations must prioritize the security of their IoT Big Data architecture. Ensuring data encryption, secure authentication, and regular vulnerability assessments are essential to safeguarding IoT data.

Data Quality: The sheer amount of data generated by IoT devices can lead to issues with data quality. Companies need to implement systems that filter out irrelevant or redundant data to ensure that only valuable insights are derived.

Scalability: As the number of connected devices grows, so does the complexity of managing IoT Big Data solutions. Businesses need scalable architectures that can handle exponential growth in data while maintaining efficiency.

The Future of IoT and Big Data

The convergence of IoT and Big Data analytics is set to drive significant advancements in many sectors, including healthcare, manufacturing, smart cities, and retail. As IoT devices become more ubiquitous, businesses will increasingly rely on IoT Big Data solutions to make data-driven decisions, improve efficiency, and create personalized experiences.

Looking ahead, the integration of artificial intelligence (AI) and machine learning with IoT will further enhance predictive capabilities, enabling even more accurate forecasting and decision-making. For instance, autonomous vehicles will rely heavily on IoT and Big Data analytics to process vast amounts of real-time data from sensors, allowing for safer and more efficient driving experiences.

Conclusion

The fusion of the Internet of Things and Big Data analytics offers unprecedented opportunities for businesses to harness the power of real-time data and make more informed, timely decisions. By implementing robust IoT Big Data architectures and integrating machine learning models, companies can derive actionable insights that lead to greater operational efficiency, improved customer experiences, and innovation across industries.

As IoT continues to evolve, businesses that invest in the right IoT Big Data solutions will be well-positioned to lead in a data-driven future.

Browse Related Blogs – 

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[tudipblog]

Beyond the Buzz: How IoT Redefines Business Operations

Moving from Hype to Reality

IoT has moved from being a futuristic idea to a practical solution that businesses use daily to improve operations and achieve sustainable growth. Though much of the discussion around IoT is about its potential, the real value that it presents is in how companies can use the technology to solve real-world problems.

Today, IoT is no longer a buzzword; it’s a necessity for any business looking to remain competitive and agile in a dynamic global environment. With its power to integrate devices, data, and processes, IoT helps businesses achieve efficiencies, improve customer satisfaction, and create new revenue streams. In this blog post, we explore how IoT is changing business operations across industries and what companies need to do to maximize its potential.

How Tudip Technologies Redefines IoT Solutions

Tudip Technologies empowers businesses with IoT solutions that tackle complex operational challenges and drive measurable outcomes.

Our Specialized Approach:

Edge Computing Integration: Enabling faster data processing closer to devices for real-time responsiveness.

IoT Ecosystem Design: Creating scalable ecosystems that adapt to changing business needs.

Sustainability-Focused Solutions: Tailoring IoT frameworks that align with environmental goals.

Example: Tudip partnered with a logistics provider to implement IoT-powered edge analytics, reducing data processing times by 60% and improving delivery accuracy across global operations.

Key Takeaways: Turning IoT Into Operational Strength

Invest in Scalable Solutions: Ensure your IoT systems can grow alongside your business needs.

Prioritize Security: Robust cybersecurity measures arToday, IoT is no longer a buzzword; it’s a necessity for any business looking to remain competitive and agile in a dynamic global environment. With its power to integrate devices, data, and processes, IoT helps businesses achieve efficiencies, improve customer satisfaction, and create new revenue streams. In this blog post, we explore how IoT is changing business operations across industries and what companies need to do to maximize its potential.

Redefining Operational Efficiency with IoT

1. Predictive Analytics: Smarter Urban Operations with IoT

IoT is revolutionizing energy management by integrating renewable energy sources into business operations. Smart systems analyze usage patterns and adjust power drawn from solar, wind, or traditional grids in real time.

Optimized Renewable Usage: IoT ensures renewable energy is used efficiently by monitoring supply-demand gaps.

Grid Stability:  Balances energy loads to prevent outages during peak hours.

Sustainability Goals: Helps businesses achieve net-zero emissions by prioritizing clean energy consumption.

Example: A technology campus integrated IoT in optimizing its solar energy consumption and reduced dependence on traditional grids by 40%, with a significant reduction in operational costs

2. Energy Management: Advancing Renewable Solutions

Predictive analytics powered by IoT is transforming urban infrastructure. Cities can now monitor critical assets like bridges, roads, and utilities in real time, ensuring timely maintenance and preventing costly failures.

Public Safety: Early detection of infrastructure stress minimizes risks to citizens.

Cost Efficiency: Avoiding large-scale repairs reduces budget overruns for municipalities.

Sustainability: Proactive maintenance extends the lifespan of assets, reducing waste.

3. Automation Excellence: Better Disaster Response Logistics

IoT-driven automation is transforming how disaster response occurs—getting aid to where it is needed, faster and more efficiently.

Real-Time Inventory Management: Monitors relief inventory and ensures its proper distribution to areas of greatest need.

Smart Transportation: Optimizes routes for rescue and supply vehicles during crises.

Collaboration Across Agencies: IoT systems enable seamless communication between response teams.

Example:In a recent hurricane, one global aid organization leveraged IoT-connected drones to survey damage and automate the delivery of supplies, resulting in a 50% faster response time.

Overcoming Common IoT Challenges

1. Integration of IoT with Existing Systems

One of the biggest hurdles businesses face is integrating IoT solutions with legacy systems. Compatibility issues can hinder seamless data exchange and functionality. Solution: Use a flexible IoT platform with built-in interoperability; make sure it provides APIs for smooth integration. Careful planning and phased implementation may also reduce disruptions to a minimum.

2. Data Security and Privacy

IoT ecosystems are all about continuous data gathering and transmission, which increases exposure to cyber threats. The security of sensitive information is the foundation of trust with stakeholders.

Solution: Implement robust encryption protocols, regularly update security measures, and educate employees on cybersecurity best practices.

3. Adapting to Rapid Technological Changes

The rapid rate of innovation in IoT can make it challenging for businesses to adapt to new developments and keep their systems current. Solution: Collaborate with technology providers that offer scalable solutions and ongoing support to adapt to emerging trends without overhauling existing systems.

How IoT Drives Operational Transformation

1. Enhancing Decision-Making with Real-Time Insights

IoT provides companies with real-time data that enables informed decision-making. Whether it is revising supply chain strategies or optimizing production schedules, IoT ensures that companies can act quickly and confidently.

Dynamic Adaptability: Businesses can change their strategies according to up-to-date information and stay responsive to market demand.

Improved Collaboration: IoT systems enable better communication across departments, enabling coordinated efforts.

2. Creating Value Through Customization

IoT’s ability to collect granular data allows businesses to tailor their offerings and services to meet specific customer needs. Personalization not only enhances user experience but also builds stronger customer relationships.

e non-negotiable in today’s interconnected world.

Focus on Outcomes: Use IoT to achieve specific goals, whether it’s reducing costs, enhancing customer satisfaction, or achieving sustainability targets.

Conclusion: Moving Beyond the Buzz

IoT has evolved into an indispensable solution, reshaping how businesses optimize operations and achieve sustainable growth. By addressing real-world challenges and delivering actionable insights, IoT enables companies to stay competitive and adaptive.

To fully realize the benefits of IoT, businesses must focus on integrating flexible solutions, safeguarding data, and aligning technology with strategic objectives. With the right approach, IoT becomes more than a technological innovation—it becomes a cornerstone of operational excellence and sustainable growth.

Click the link below to learn more about the blog Beyond the Buzz: How IoT Redefines Business Operations

https://tudip.com/blog-post/beyond-the-buzz-how-iot-redefines-business-operations/

[charlessmithpost]

The Internet of Things (IoT) enhances Business Intelligence (BI) by providing real-time data collection and analysis. This leads to improved decision-making, operational efficiency, and predictive analytics. Businesses can monitor assets, optimize processes, and better understand customer behavior, driving innovation and competitive advantage.

[techtoio]

Emerging Tech Trends in the Internet of Things (IoT)

Introduction

The Internet of Things (IoT) is transforming our world by connecting devices and enabling smarter, more efficient interactions. In everything from smart homes to industrial automation, the IoT is leading a revolution in our living and working environments. In this article, TechtoIO explores the emerging tech trends in IoT, highlighting the innovations and advancements that are shaping the future. Read to continue link

[debajitadhikary]

10 Most important Technologies that IT Advisors use to Navigating the Future of Information Technology

Introduction as IT Advisors In the dynamic realm of Information Technology (IT), staying ahead requires a powerful arsenal of cutting-edge technologies. IT advisors, the guiding force behind digital transformations, leverage a spectrum of tools to optimize operations, enhance security, and propel their clients into the future. In this exploration, we’ll delve into the tech landscape that…

[i4technolab]

In today’s fast-paced world of logistics innovation and evolution have become the driving forces behind success. As we step into 2024, the logistics sector will undergo extensive disruptions, fueled by game-changing innovations that promise to revolutionize supply chain management as we know it.

At iFour, we take immense pride in our expertise in the logistics industry, and we are excited to share with you the trends that are currently transforming this dynamic sector in Australia. As a leading custom Logistics software development company, we understand the unique challenges and opportunities facing businesses in the Australian market.

Here are the key trends that are reshaping the logistics landscape and how our solutions can help your company stay ahead of the curve.

[techobase]

[marketxcel]

The Future of Market Research: Unveiling the Top 10 Emerging Trends

The landscape of market research is undergoing a transformative shift, driven by the convergence of technology, consumer behavior, and data-driven insights. Embracing these six emerging trends empowers businesses to connect with their target audiences on a deeper level, adapt to changing market dynamics, and make informed decisions that drive success

[nuadox]

nami secures $10.5M Series A for its multi-sensing platform

- By Nuadox Crew -

Singapore-based nami, a multi-sensing platform and ecosystem enabler for the Internet of Things (IoT) industry, has announced the successful closure of its Series A financing round. 

The company raised $10.5 million from strategic investors, including Verizon Ventures, Amavi Capital, INSPiRE, and Aconterra. 

nami's platform allows enterprise customers to quickly deploy intelligent IoT services by processing raw sensor data, converting it into actionable metadata, and using it to trigger automation across the entire IoT environment. 

With the funding, nami plans to expand its team and geographical presence to deploy its digital sensing infrastructure across residential and commercial buildings on three continents. The company aims to build an ecosystem of AI sensors catering to various industries, such as IoT players, internet service providers, and insurance companies.

--

Source: nami

Read Also

Survey: 2 in 3 US homeowners use smart home devices to monitor their home

[very-gay-alkyrion]

You know how Greta Thunberg said "You have stolen our dreams"?

This is how I feel about Sam Altman and AI.

I was *robbed* of a future where AI is a cool tool, instead of yet another shiny, meaningless tech buzzword, and a shit feature that nobody wants to increase sales. Instead of something to help us better diagnose cancer, we are setting the planet on fire and completely disregarding anything Hayao Miyazaki has said about how he feels about AI, all just to see how we'd look as Studio Ghibli characters.

You see, I study AI. But I applied before the whole ChatGPT thing. At the time, OpenAI let a few select people prompt GPT-3. To generate YouTube titles and that sort of thing.

Back then, AI was mostly used for analytical purposes. To detect fires early, to help analyze protein folding, to develop new medication. And this was what drew me in.

When ChatGPT hit the scenes, I was genuinely excited for the potential of it. For the potential to make the internet more accessible, to be used for good.

Oh, how naïve I was back then.

Instead of that, AI is - in the best case scenario - used as yet another meaningless tech buzzword. It infests any product of any company that has nothing else to offer.

And that is the best case scenario. In the average case, instead of just being enshittification itself, it helps to accelerate enshittification by generating meaningless slop to poison search results, both in text and in picture form.

In the worst case scenario, AI is actively being used for harm. Used to generate nonconsensual imagery of people. Used as a tool for misinformation, for manipulating the public opinion, not only enshittifying the internet, but actively making it a worse, more hostile, more adverse place.

And that does not even touch on the issue of how training data is gathered, and the legal and ethical problems this raises, which, I hope, being on Tumblr, you're all well aware of by now. To any artist, I fully support you using nightshade to actively poison your work.

So yes. Despite being a student of AI, I am disgusted with what this field has become.

The following paragraphs are directed at anyone who has worked or currently works on any generative AI system:

You have stolen my dreams.

Not only have you stolen my dreams, you have plundered them for every dollar, every cent, against any moral or ethical code, in search of profits over everything.

You are going against every moral code that people should be committed to. But you don't care, as long as you can make a quick buck.

You don't care if Hayao Miyazaki has called generative AI "an insult to life itself". You just want to see yourself in the Studio Ghibli style, because to you, everything, even art, is something to be commoditized, to be mass-produced just so it can be instantly forgotten.

FUCK YOU AND THE MECHANICAL HORSE YOU RODE IN ON.

[blanket-fish]

Generative AI is bad "I agree, there's only a few good use cases" no there are no good use cases, it's regularly wrong and plagiarises anything on the internet "It's not plagiarism, when I ask it to write a paragraph it's my words!" No it is not, and don't you give a single shit about what you're writing?? "Lmao who cares about cover letters and emails?" There are six bajillion online templates for those things. "this is so true, I only use it for school essays" that's preventing yourself from learning anything "Oh so now the school system is perfect huh?" Depriving yourself of the one good thing it does does not improve the system "This!! People need to stop using chatgpt for school! I only use it as a newsfeed :)" there are no good use cases "okay but my lab uses it to analyse medical data, is it bad for AI to save lives OP?" This post is about generative AI, not analytical AI, which is very different "Yeah, analytical AI is great! I use it to sum up books into bullet points so I don't have to read them" that is still generative AI and why would you do that? That post about chatgpt petting your dog for you was a joke "it's harder for some people to read books, ableist" ??? There are cliffnotes versions of most books, which are written by actual people, and will actually convey a book well. "Yeah! Actually read books! Chatgpt is only good for-"

[the-empress-7]

Do you genuinely see stuff about the Harkles outside of the internet? I feel like their coverage has dropped massively while you were gone did stuff about them come up organically?

Great question anon! As you know I took a major step back from royal watching the past few months, but it's not the first time I have taken a break in the many years I have been following this mess. During this most recent break the difference was stark, not once did the Harkles break through organically into my "normal" media consumption. Catherine did, many times over, as did William and their children.

This most recent IG games validated things for me in a big way. I was lucky enough to be away on a business trip on the other side of the planet for almost the entirety of the games. Not only did nothing break through, I also had a really hard time trying to find information on it via my usual methods. The only accounts that delivered were the hardcore Megxit accounts who pour over everything they do, and even they posted sparingly (relatively speaking).

Her return to Insta kind of made the news, but even then barely. It was nowhere near the level of attention that Catherine has gotten no matter what she has done in the past year. I bet that has Meghan spitting nails.

I don't have access to Google analytics, but if someone does I'd love to see the data for the trends on MM. I remember when @anonymoushouseplantfan used to share the info, and it was all flatlining even back in 2022.

[sheevangiiiii]

Melodies, Memory, and a Mouse Click: How One Direction Became the Soundtrack of My Digital Childhood

In 2012, I was a seven-year-old girl living in the warmth of an Indian household, where school uniforms, steel tiffin boxes, and summer vacations filled with board games were the core of everyday life. One ordinary afternoon, while sitting beside my cousin, I clicked on a YouTube video titled “What Makes You Beautiful.” That single click unknowingly introduced me to a band called One Direction—a name that would stay etched in my memory for years. Their songs quickly became part of my routine: echoing softly while I made greeting cards, humming along during power cuts, and playing quietly in the background as I rehearsed dance steps for school functions. Without me realizing it, One Direction became more than music—it became a part of the rhythm of my childhood.

A Digital Memory Lane Before smartphones became extensions of our hands and before reels flooded our screens, discovering content online felt magical. I still remember waiting for the internet to connect, the buffering circle spinning endlessly, and the excitement of finally watching a music video load. My One Direction phase wasn’t defined by social media trends or fandom edits but by playlists burned onto CDs and MP3 players borrowed from my father’s drawer. Their songs traveled with me—from my room to long car journeys—and marked milestones in my early years. It wasn’t about idolizing celebrities; it was about finding comfort in familiarity. The music stitched itself into the fabric of my growing-up years, becoming a quiet but constant companion.

Emotional Anchors in Digital Spaces In today’s academic discourse, digital communication is often evaluated through the lens of productivity, virality, and engagement. But in the quieter corners of the internet lie its emotional footprints—the small, personal interactions that shape our inner world. For me, One Direction’s music videos, behind-the-scenes clips, and even lyric slideshows on YouTube served as gentle emotional anchors. Their cheerful melodies uplifted my moods on dull days, while slower ballads comforted me in ways I couldn’t explain as a child. Psychologists now speak of how digital content can influence emotional development in children, and my story reflects that in the most subtle, lived way. That music taught me rhythm, English phrases, and above all, the feeling of calm in chaos.

A Bridge Across Time Even today, when I accidentally hear “Little Things” or “Story of My Life”, I’m transported back—not to a concert or an award show, but to my study table, my childhood bedroom, and to the smell of freshly sharpened pencils. Digital memories are powerful that way—they create time capsules of emotion. As I step into adulthood and deeper into the academic study of digital communication, I realise that some of the strongest digital imprints are not in data analytics or AI trends, but in the songs that played softly in the background of our lives.

Conclusion: In the grand world of digital communication, it’s easy to focus on innovation and metrics. But sometimes, it’s important to acknowledge the deeply personal side of the digital age—how a simple YouTube video can spark a lifelong memory, how music can wrap around a childhood like a warm blanket. My One Direction phase was not a fandom frenzy, but a quiet chapter in my story—a reminder that behind every click, stream, and download, there often lies something far more human: comfort, connection, and a sense of home.

[river-taxbird]

The Four Horsemen of the Digital Apocalypse

Blockchain. Artificial Intelligence. Internet of Things. Big Data.

Do these terms sound familiar? You have probably been hearing some or all of them non stop for years. "They are the future. You don't want to be left behind, do you?"

While these topics, particularly crypto and AI, have been the subject of tech hype bubbles and inescapable on social media, there is actually something deeper and weirder going on if you scratch below the surface.

I am getting ready to apply for my PhD in financial technology, and in the academic business studies literature (Which is barely a science, but sometimes in academia you need to wade into the trash can.) any discussion of digital transformation or the process by which companies adopt IT seem to have a very specific idea about the future of technology, and it's always the same list, that list being, blockchain, AI, IoT, and Big Data. Sometimes the list changes with additions and substitutions, like the metaverse, advanced robotics, or gene editing, but there is this pervasive idea that the future of technology is fixed, and the list includes tech that goes from questionable to outright fraudulent, so where is this pervasive idea in the academic literature that has been bleeding into the wider culture coming from? What the hell is going on?

The answer is, it all comes from one guy. That guy is Klaus Schwab, the head of the World Economic Forum. Now there are a lot of conspiracies about the WEF and I don't really care about them, but the basic facts are it is a think tank that lobbies for sustainable capitalist agendas, and they famously hold a meeting every year where billionaires get together and talk about how bad they feel that they are destroying the planet and promise to do better. I am not here to pass judgement on the WEF. I don't buy into any of the conspiracies, there are plenty of real reasons to criticize them, and I am not going into that.

Basically, Schwab wrote a book titled the Fourth Industrial Revolution. In his model, the first three so-called industrial revolutions are:

1. The industrial revolution we all know about. Factories and mass production basically didn't exist before this. Using steam and water power allowed the transition from hand production to mass production, and accelerated the shift towards capitalism.

2. Electrification, allowing for light and machines for more efficient production lines. Phones for instant long distance communication. It allowed for much faster transfer of information and speed of production in factories.

3. Computing. The Space Age. Computing was introduced for industrial applications in the 50s, meaning previously problems that needed a specific machine engineered to solve them could now be solved in software by writing code, and certain problems would have been too big to solve without computing. Legend has it, Turing convinced the UK government to fund the building of the first computer by promising it could run chemical simulations to improve plastic production. Later, the introduction of home computing and the internet drastically affecting people's lives and their ability to access information.

That's fine, I will give him that. To me, they all represent changes in the means of production and the flow of information, but the Fourth Industrial revolution, Schwab argues, is how the technology of the 21st century is going to revolutionize business and capitalism, the way the first three did before. The technology in question being AI, Blockchain, IoT, and Big Data analytics. Buzzword, Buzzword, Buzzword.

The kicker though? Schwab based the Fourth Industrial revolution on a series of meetings he had, and did not construct it with any academic rigor or evidence. The meetings were with "numerous conversations I have had with business, government and civil society leaders, as well as technology pioneers and young people." (P.10 of the book) Despite apparently having two phds so presumably being capable of research, it seems like he just had a bunch of meetings where the techbros of the mid 2010s fed him a bunch of buzzwords, and got overly excited and wrote a book about it. And now, a generation of academics and researchers have uncritically taken that book as read, filled the business studies academic literature with the idea that these technologies are inevitably the future, and now that is permeating into the wider business ecosystem.

There are plenty of criticisms out there about the fourth industrial revolution as an idea, but I will just give the simplest one that I thought immediately as soon as I heard about the idea. How are any of the technologies listed in the fourth industrial revolution categorically different from computing? Are they actually changing the means of production and flow of information to a comparable degree to the previous revolutions, to such an extent as to be considered a new revolution entirely? The previous so called industrial revolutions were all huge paradigm shifts, and I do not see how a few new weird, questionable, and unreliable applications of computing count as a new paradigm shift.

What benefits will these new technologies actually bring? Who will they benefit? Do the researchers know? Does Schwab know? Does anyone know? I certainly don't, and despite reading a bunch of papers that are treating it as the inevitable future, I have not seen them offering any explanation.

There are plenty of other criticisms, and I found a nice summary from ICT Works here, it is a revolutionary view of history, an elite view of history, is based in great man theory, and most importantly, the fourth industrial revolution is a self fulfilling prophecy. One rich asshole wrote a book about some tech he got excited about, and now a generation are trying to build the world around it. The future is not fixed, we do not need to accept these technologies, and I have to believe a better technological world is possible instead of this capitalist infinite growth tech economy as big tech reckons with its midlife crisis, and how to make the internet sustainable as Apple, Google, Microsoft, Amazon, and Facebook, the most monopolistic and despotic tech companies in the world, are running out of new innovations and new markets to monopolize. The reason the big five are jumping on the fourth industrial revolution buzzwords as hard as they are is because they have run out of real, tangible innovations, and therefore run out of potential to grow.

[fullofmultitudesfullofshit]

i've been thinking about AI a lot lately, and i know a lot of us are, it's only natural considering that it's forced onto us 24/7 by most search engines, pdf readers, & microsoft and apple, but i think what is increasingly making me crazy, as an academic, college teacher, and grad student, is the forcible cramming of it into our everyday lives and social institutions.

no one asked for this technology -- and that's what's so alarming to me.

technology once RESPONDED to the needs and intuitions of a society. but no one needed AI, at least not in the terrifying technocratic data mining atrophying cognitive thought that it's evolving into, and no asked for this paradigm shift to a digital shitty algorithm that we don't understand.

it's different from when the iphone came out and started a revolution where pretty much everyone needed a smartphone. there was an integration -- i remember the first iphone commercial and release news. it wasn't so sudden, but it was probably inevitable given the evolution of the internet and technology that everyone would have a smartphone.

what i know about AI is this: from the first 6 months of ChatGPT's release, they have tried to say it is INEVITABLE.

I walked into my classroom in Fall of 2023 to a room full of 18 year-olds, and suddenly, they were all using it. they claimed it helped them "fill in the gaps" of things they didn't understand about writing. i work with 4th year college students applying to med school -- they use "chat" to help them "come up with sentences they couldn't come up with on their own." i work with a 3rd year pharmacy school student applying to a fellowship who doesn't speak english as a primary language and he's using "AI to sound more American." i receive a text from an ex-boyfriend about how he 'told ChatGPT to write a poem about me.' (it's supposed to be funny. it's not.) i'm at a coffee shop listening to two women talk about how they use ChatGPT to write emails and cut down on the amount of hours they do everyday. i scroll past an AI generated advertisement that could have been made with a graphic designer. i'm watching as a candidate up for the job of the new dean to the college of arts and sciences at my university announces that AI should be the primary goal of humanities departments -- "if you're a faculty member and you're not able to say how you USE AI in your classroom, then you're wasting the university's time and money." i'm at a seminar in DC where colleagues of mine -- fellow teachers and grad students -- are exclaiming excitedly, "I HATE AI don't get me wrong, but it's helpful for sharpening my students' visual analytical skills." i'm watching as US congressional republicans try to pass a law that puts no federal oversight on AI for ten years. i'm watching a YouTube video of a woman talking about Meta's AI data center in her backyard that has basically turned her water pressure to a trickle. i'm reading an article about how OpenAI founder, Sam Altman, claims that ChatGPT can rival someone with a PhD. i'm a year and half away, after a decade of work, from achieving a PhD.

billionaires in silicon valley made us -- and my students -- think that AI is responding to a specific technological dearth: it makes things easier. it helps us understand a language we don't speak. it helps us write better. it helps us make sense of a world we don't understand. it helps us sharpen our skills. it helps us write an email faster. it helps us shorten the labor and make the load lighter. it helps us make art and music and literature.

the alarming thing is -- it is responding to a need, but not the one they think. it's responding to a need that we are overworked. it's responding to a need that the moral knowledge we need to possess is vast, complicated, and unknowable in its entirety. it's responding to a need that emails fucking suck. it's responding to a need that art and music, which the same tech and engineering bros once claimed were pointless ventures, are hard to think about and difficult to create. it's responding to the need that we need TIME, and in capitalism, there is rarely enough for us to create and study art that cannot be sold and bought for the sake of getting someone rich.

AI is not what you think it is -- of course, it is stupid, it is dumb, and i fucking hate it as much as the next guy, but it is a red fucking flag. not even mentioning the climate catastrophe that it's fast tracking, AI tech companies by and large want us to believe that there isn't time, that there isn't a point to doing the things that TAKE time, that there isn't room for figuring out things that are hard and grey and big and complicated. BUT WORTH, FUCKING, DOING.

but there is. THERE ALWAYS IS. don't let them make you think that the work and things you love are NOT worth doing. AI is NOT inevitable and it does NOT have to be the technological revolution that they want us to think it is.

MAKE ART.

ASK QUESTIONS.

STUDY ART.

DO IT BAD; DO IT SHITTY.

FUCK AI FOREVER.