Future technology: 22 ideas about to change our world

Technology moves at a relentlessly fast pace in the modern world. It can sometimes feel like every single day there are new technologies and innovations that will change our futures forever. But in a steady stream of announcements about new massive futuristic technological upgrades and cool gadgets, it is easy to lose track of the amazing ways the world is progressing.

For instance, there are artificial intelligence programs writing poems from scratch and making images from nothing more than a worded prompt. There are 3D-printed eyes, new holograms, lab-grown food and brain-reading robots.

All of this just scratches the surface of what is out there, so we’ve curated a guide to the most exciting future technologies, listing them all below.

Necrobotics

© Preston Innovation Laboratory/Rice University
© Preston Innovation Laboratory/Rice University

Sometimes new future technologies can offer amazing development, with the possibility of changing the future… while also being incredibly creepy.

This is one way to describe the idea of necrobotics which, as the name suggests, involves turning dead things into robots. While this sounds like a plot to a creepy horror film, this is a technology being explored at Rice University.

A team of researchers turned a dead spider into a robot-like gripper, given the ability to pick up other objects. To achieve this, they take a spider and inject it with air. This works because spiders use hydraulics to force their version of blood (haemolymph) into their limbs, making them extend.

Right now this concept is in its infant stages, but it could mean a future where dead animals are used to further science… it all feels very Frankeinstein-like!

Sand batteries

© Edwin Remsberg
© Edwin Remsberg

Not every technology bettering our future has to be complicated, some are simple, yet extremely effective.

One of these kind of technologies has come from some Finnish engineers who have found a way to turn sand into a giant battery.

These engineers piled 100 tons of sand into a 4 x 7 metre steel container. All of this sand was then heated up using wind and solar energy.

This heat can then be distributed by a local energy company to provide warmth to buildings in nearby areas. Energy can be stored this way for long periods of time.

All of this occurs through a concept known as resistive heating. This is where a material is heated by the friction of electrical currents.

Sand and any other non-super conductor are warmed by the electricity passing through them generated heat than can be used for energy.

E-skin could help us hug long-distance friends

While modern technology allows us to communicate verbally and visually almost anywhere in the world, there is currently no reliable method of sharing the sense of touch across long distances. Now, a wireless soft e-skin developed by engineers at the City University of Hong Kong could one day make giving and receiving hugs over the internet a reality.

The e-skin is studded with flexible actuators that sense the wearer’s movements and convert them into electrical signals.

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How generative AI could change your business enterprise

In the spirit of this article’s matter, we requested ChatGPT—a generative AI language design that can develop primary written content in response to a user prompt—how it would set the context. Our prompt to the method:

Produce the opening paragraph for an short article about how transformative generative AI will be for business, in the style of McKinsey & Enterprise.

ChatGPT’s reaction:

The rise of generative AI has the prospective to be a main video game-changer for enterprises. This technology, which will allow for the creation of original information by understanding from current facts, has the energy to revolutionize industries and change the way businesses work. By enabling the automation of a lot of responsibilities that were being beforehand finished by individuals, generative AI has the probable to boost performance and productivity, decrease fees, and open up up new alternatives for advancement. As this kind of, corporations that are ready to effectively leverage the technological know-how are probably to achieve a important competitive edge.

Not best but overwhelmingly impressive.

For us and numerous executives we’ve spoken to not too long ago, moving into a single prompt into ChatGPT, developed by OpenAI, was all it took to see the electric power of generative AI. In the 1st 5 days of its release, far more than a million users logged into the platform to working experience it for themselves. OpenAI’s servers can scarcely retain up with demand, routinely flashing a concept that customers need to have to return afterwards when server capacity frees up.

Merchandise like ChatGPT and GitHub Copilot, as well as the underlying AI styles that energy these devices (Secure Diffusion, DALL·E 2, GPT-3, to title a couple), are having technological innovation into realms as soon as imagined to be reserved for people. With generative AI, personal computers can now arguably exhibit creativeness. They can make initial information in reaction to queries, drawing from details they’ve ingested and interactions with people. They can acquire blogs, sketch offer layouts, create computer code, or even theorize on the rationale for a creation mistake.

This most recent class of generative AI systems has emerged from basis models—large-scale, deep finding out designs trained on enormous, broad, unstructured information sets (this kind of as textual content and pictures) that include a lot of matters. Builders can adapt the styles for a wide range of use scenarios, with minor great-tuning expected for each activity. For instance, GPT-3.5, the foundation design underlying ChatGPT, has also been applied to translate textual content, and scientists used an previously variation of GPT to produce novel protein sequences. In this way, the electrical power of these capabilities is accessible to all, like developers who absence specialized device finding out expertise and, in some circumstances, people today with no specialized track record. Using foundation designs can also minimize the time for establishing new AI applications to a degree hardly ever possible before.

Generative AI guarantees to make 2023 one particular of the most exciting many years however for AI. But as

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Influence of green technology, green energy consumption, energy efficiency, trade, economic development and FDI on climate change in South Asia

  • Kejun, J. et al. Transition of the Chinese economy in the face of deep greenhouse gas emissions cuts in the future. Asian Econ. Policy Rev. 16(1), 142–162 (2021).

    Article 

    Google Scholar
     

  • COP26, United nations climate change. https://unfccc.int/news/cop26-facts-and-figures, (2020).

  • Dong, Y., Coleman, M. and Miller, S. A. Greenhouse gas emissions from air conditioning and refrigeration service expansion in developing countries. Annual Rev. Environ. Resour. 46 (2021).

  • Azam, M. & Khan, A. Q. Testing the Environmental Kuznets Curve hypothesis: A comparative empirical study for low, lower middle, upper middle and high income countries. Renew. Sustain. Energy Rev. 63, 556–567 (2016).

    CAS 
    Article 

    Google Scholar
     

  • Li, Z. et al. An economic analysis software for evaluating best management practices to mitigate greenhouse gas emissions from cropland. Agric. Syst. 186, 102950 (2021).

    Article 

    Google Scholar
     

  • Dinda, S. Environmental Kuznets curve hypothesis: A survey. Ecol. Econ. 49(4), 431–455 (2004).

    Article 

    Google Scholar
     

  • Xia, Q. et al. Drivers of global and national CO2 emissions changes 2000–2017. Climate Policy 21(5), 604–615 (2021).

    Article 

    Google Scholar
     

  • Fatima, T., Shahzad, U. & Cui, L. Renewable and nonrenewable energy consumption, trade and CO2 emissions in high emitter countries: Does the income level matter?. J. Environ. Planning Manage. 64(7), 1227–1251 (2021).

    Article 

    Google Scholar
     

  • Kılavuz, E. & Doğan, İ. Economic growth, openness, industry and CO2 modelling: Are regulatory policies important in Turkish economies?. Int. J. Low-Carbon Technol. 16(2), 476–487 (2021).

    Article 

    Google Scholar
     

  • Setyari, N. P. W. & Kusuma, W. G. A. Economics and environmental development: Testing the environmental Kuznets Curve hypothesis. Int. J. Energy Econ. Policy 11(4), 51 (2021).

    Article 

    Google Scholar
     

  • Gołasa, P. et al. Sources of greenhouse gas emissions in agriculture, with particular emphasis on emissions from energy used. Energies 14(13), 3784 (2021).

    Article 

    Google Scholar
     

  • Liobikienė, G. & Butkus, M. The challenges and opportunities of climate change policy under different stages of economic development. Sci. Total Environ. 642, 999–1007 (2018).

    ADS 
    PubMed 
    Article 

    Google Scholar
     

  • Koondhar, M. A. et al. A visualization review analysis of the last two decades for environmental Kuznets curve “EKC” based on co-citation analysis theory and pathfinder network scaling algorithms. Environ. Sci. Pollut. Res. 28(13), 16690–16706 (2021).

    CAS 
    Article 

    Google Scholar
     

  • Bilgili, F., Koçak, E. & Bulut, Ü. The dynamic impact of renewable energy consumption on CO2 emissions: A revisited Environmental Kuznets Curve approach. Renew. Sustain. Energy Rev. 54, 838–845 (2016).

    Article 

    Google Scholar
     

  • Gorus, M. S. & Aydin, M. The relationship between energy consumption, economic growth, and CO2 emission in MENA countries: Causality analysis in the frequency domain. Energy 168, 815–822 (2019).

    Article 

    Google Scholar
     

  • Kirikkaleli, D. & Adebayo, T. S. Do renewable energy consumption and financial development matter for environmental sustainability? New global evidence. Sustain. Develop. 29(4), 583–594 (2021).

    Article 

    Google Scholar
     

  • Godil, D. I. et al. Investigate the role of technology innovation and renewable energy in reducing transport sector CO2 emission in China: A path toward sustainable development. Sustain. Develop. (2021).

  • An, T., Xu, C. &

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    How AI will change the future of search engine optimization

    As artificial intelligence (AI) becomes more sophisticated, search engine optimization will have to adapt. AI can already analyze data at a rate that humans can’t, so it’s only a matter of time until it starts to dominate SEO strategies.

    The SEO industry is always in a state of flux. Google is constantly changing its algorithms, and new technologies are emerging all the time. Ever since Google’s announcement in 2015 that they would be using RankBrain, an artificial intelligence (AI) system, to help process search results, the SEO community has been discussing the impact that AI will have on the industry.

    RankBrain is not the only AI system that Google is using. In 2017, they announced that they were also using machine learning to fight spam.

    Since Google’s Search Liaison, Danny Sullivan, confirmed in 2019 that RankBrain was now being used for every search query, several companies have started to experiment with AI and machine learning to try and get ahead of the curve. This gave rise to a whole new plethora of AI-based SEO tools. Some of the prominent ways in which AI tools have proven their effectiveness are SEO keyword research, content creation, traffic and site growth analysis, voice search, and SEO workflows.

    These applications have made it evident that the future of SEO is in Artificial Intelligence. The question is not whether AI will change SEO but how soon it will happen. The number of companies interested in AI-based SEO has increased significantly in the past year and is only going to grow in the years to come.

    “I think we’re going to see a continued move towards more personalized search results, and that will be driven by both better use of data as well as machine learning models.  I also believe we’ll start to see Google put more emphasis on entities, rather than just keywords, as they continue to try and better understand the searcher’s intent,” said Rand Fishkin, founder of Moz.

    Here’s how AI is already changing SEO and how we can expect it to change even more in the future.

    Keywords and anchor management

    SEO keyword research is one of the most important aspects of SEO. It has always been a time-consuming and tedious task, but AI tools have made it much easier. AI-based keyword capabilities like SEO Vendor’s AI Analysis assist in analyzing anchor text usage, keyword variations and semantic keywords.

    Content creation and analysis

    Content is still the king when it comes to SEO. Google’s algorithm uses natural language processing (NLP) to understand the content on a webpage and match it with the user’s query. This means that creating high-quality, relevant content is more important than ever before.

    In spite of heated debates over Google’s reaction to generated content, we continue to see a greater introduction of tools based on GPT-3, and GPT-4 development is well underway.

    Traffic and ranking growth analysis

    Understanding your website’s rankings and traffic growth is essential for SEO. Google Analytics is a great tool for this, but it

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