Researchers at Binghamton University in New York have developed a new bio-battery that uses bacteria to generate electricity. The sustainable battery apparently has a performance of several weeks.
Scientists at New York’s Binghamton University have developed a new bio-battery that uses bacteria to generate electricity. This means that the batteries come without lithium or rare earths.
This is how the sustainable bio battery works
The bio-battery from the Seokheun Choi Electronics and Computers Laboratory uses three bacteria to generate energy. They are located in three separate, vertical chambers. They are square and about three centimeters in size.
“A photosynthetic bacterium produces organic food that is used as a nutrient for the other bacterial cells below. At the bottom is the electricity-producing bacterium, and the middle bacterium makes some chemicals to enhance electron transfer,” explains Choi.
In addition, the bio-battery can supply electricity for weeks. The sustainable battery is based on a so-called “plug and play” principle. This means that multiple bio batteries can be stacked and wired together.
Bio-battery powers small devices for weeks
Above all, Choi’s sustainable battery is intended to be an answer to how electricity can also reach remote places. In addition, small electronic devices and AIs require an autonomous energy supply around the clock.
That’s why Chois’ goal is to keep the battery small. “We call this intelligent dust and a few bacterial cells can generate enough energy to run it,” says the professor. The dust can then be scattered anywhere as needed.
In the future, Choi also wants to develop a battery pack that can float on water and manage itself. So if damage occurs in harsh environments, they will receive automatic repair.
According to forecasts by the Green Software Foundation, information and communication technology will account for around 20 percent of all electricity consumption by 2030. Emissions from digital technologies will double by 2025 compared to 2019 levels.
But the technology industry is becoming increasingly aware of its carbon footprint. Last but not least, against the background of the energy crisis, the importance of green IT is becoming increasingly apparent.
Green IT summarizes all measures that combine technological progress with environmental protection. A distinction is made between Green by IT and Green in IT. Green by IT are technologies that actively help to achieve sustainability goals. Such as software that makes consumption measurable and shows potential for optimization. Green in IT, on the other hand, aims to optimize IT processes. So that they have the least possible negative or even positive impact on the environment and resources.
This is not primarily about limitations, but about responsible and resource-saving use of technology. The greatest possible benefit should be obtained from every gram of CO₂ emitted into the atmosphere. This enables the demand shaping principle in software development.
Demand shaping
Demand shaping is a strategy to influence demand to match existing supply. Accordingly, when supply is low, demand is reduced and increases with supply accordingly. An example of this is video conferencing. When the user has low bandwidth, the video quality is reduced while the essential audio quality remains high. Demand (video quality) is adjusted to match supply (bandwidth).
Another example of demand adaptation is progressive enhancement in web design. The most basic form of a website is made available for older browsers and with low bandwidth. The more resources and bandwidth a user has available on their device, the more features are provided. But these are optional.
This principle can also be used to achieve energy efficiency. The energy requirements of applications are matched to availability. Demand shaping is therefore opposed to the widespread over-provisioning principle of providing more resources than are necessary to cover peak loads or increasing demand.
Through demand shaping, so-called “eco modes” can be built into software applications. Similar to those in cars and household appliances. The application can be used in an emissions-friendly way at the expense of performance or at full power with higher energy consumption. Applications can either be set to eco mode by default, or users can choose. Based on the nudging principle.
Another example of sustainable applications are applications optimized for edge computing. Data and process steps or complete applications are brought closer to the users instead of being processed in remote data centers. This not only reduces latency, but also CO₂ emissions, since less energy is required to transmit the data.
Renewable energy
Applications can also be programmed in such a way that the respective mode – energy saving or maximum performance – is made dependent on the availability of renewable energies.
Demand shaping is thus related to the principle of demand shifting, i.e. the shifting of demand. Here the demand for computing, storage or network resources is shifted to other regions or to times when the availability of renewable energies is higher. Companies should rely on solutions that automatically move computing, storage and network resources to where the carbon footprint is lowest.
Both demand shaping and demand shifting are important to reduce CO₂ consumption in IT. Depending on the application, developers should determine whether the computing power of applications should be reduced or relocated if the CO₂ intensity is high.
The more powerful Playstation 5 Pro is to come. Now a leak gives an idea of the time frame. Before that there will probably be a new standard PS5.
Image: Sony, Sony Playstation 5 (PS5) Artwork.
There have been rumors for a long time about a more powerful version of the Playstation 5. It will probably like the PS4 carry the name suffix Pro. Now the usually very well informed US journalist Tom Henderson has confirmed that Sony is working on such a console: The reports are “100 percent” correct.
While that doesn’t mean the PS5 Pro will actually launch. After all Sony could opt for a different business strategy. But it’s very likely.
Henderson reports on the Insider Gaming website that the manufacturer’s internal development studios should receive the first devkit prototypes within the next few months.
External studios should get the devkits towards the end of 2023. Henderson estimates that the PS5 Pro will appear in late 2024. Then the game developers would have had about a year to adapt their games to the new and basically compatible hardware.
Henderson also writes again that a new version of the Playstation 5 should be launched in the course of 2023. This is not a Slim like the ones seen in previous generations of consoles, but an only slightly modified PS5, to which an external drive can be connected if necessary.
Playstation 5: buy now or wait?
If you are thinking about buying a Playstation 5 that is currently available for immediate delivery, it is not that easy given the leaks. If you want to play the latest releases, it’s probably not worth waiting for the overhauled stock PS5.
According to the current state of information, the new console version should hardly take up less space and only have a moderately reduced power consumption. The next first-party title from Sony itself is not expected until the end of 2023 and it should be Spider-Man 2.
After delays, a preliminary version of Apple Pay Later has now been launched for selected users in the USA. This should be able to split payments into four installments.
Apple Pay users can now also pay in installments – at least in the USA. There, the tech giant from Cupertino has now launched a pre-version of Apple Pay Later. This was announced by Apple via a company announcement .
You can now pay in installments with Apple Pay. (Photo: nikkimeel/Shutterstock)
Pre-release version for select US customers only
However, even in the United States, initially only randomly selected users can benefit. You will receive an invitation for the pre-release version. Customers who want to enjoy this experience in the US must also have an iPhone with the recently released iOS 16.4 or an iPad with iPadOS 16.4.
It is not yet clear when the full version will start in the USA. Apple is talking about the next few months.
Apple had already presented Pay Later in June 2022 at the Worldwide Developers Conference 2022. However, due to delays caused by alleged technical problems, the playout was pushed back. Then, earlier this year, Apple tested the feature in beta, first by employees and then by retail staff.
This is how installment payments via Apple Pay work
With Apple Pay Later, users can split payments into up to four installments. These must be paid within six weeks. Interest and fees do not apply. In theory, you can pay at all retailers that support Apple Pay.
The loans that can be applied for through Pay Later range from a minimum of $50 to a maximum of $1,000. According to Apple, a “gentle credit check” runs in the background for every transaction.
Refunds can only be processed via debit cards. Credit cards are not accepted as they could send customers deeper into a credit spiral.
Management of installments via Apple Wallet
Users can track and manage when the installments are due via Apple Wallet. Pay Later is fully integrated into the app. Just before the installments are due, Wallet sends a notification to the user.
To ensure security and privacy, Apple Pay Later authenticates transactions via Face ID, Touch ID, or passcode.
The powerful language model ChatGPT generates texts that can hardly be distinguished from those of human authors. We explain the technology behind the hype.
Since the US company OpenAI released its new artificial intelligence (AI) ChatGPT for free testing at the end of November last year, users on social media have been sharing masses of examples of how the chatbot answers knowledge questions, formulates e-mails, writes poems or texts summarizes.
ChatGPT’s ability to confidently deal with natural language and to understand complex relationships with a high hit rate is seen by some observers as another milestone on the way to strong artificial intelligence – i.e. to algorithms that are on a par with human thinking ability in every respect. But how does the technology that makes all this possible work?
Six years – an AI eternity
ChatGPT is a language model, i.e. a machine learning algorithm that specializes in processing texts. ChatGPT is the latest generation in a series of language models based on the so-called Transformer model introduced in 2017. The Transformer architecture caused a stir when it was released in professional circles because it enabled specialized language models for text translation and other tasks with unprecedented power.
Instead, the GPT model was pre-trained on very large data sets of generic texts in order to learn statistical properties of language as such independently of the specific task. The model prepared in this way could then be effectively adapted with smaller sets of sample data for specific tasks.
The next version GPT-2 appeared in 2019 (PDF) . It was essentially a scaled-up version of the previous model with a significantly higher number of parameters and with training on correspondingly larger data sets. In contrast to the original version, GPT-2 was no longer adapted for special problems, but was able to solve many different tasks such as translating texts or answering knowledge questions simply by training with generic texts from the Internet.
With 175 billion parameters, the third generation GPT-3 (PDF) was even more extensive than GPT-2 and correspondingly more powerful. It also attracted attention beyond the AI research community, particularly with its ability to write longer texts that were almost indistinguishable from those of human authors.
However, limitations of the model also became apparent, including ethical issues with objectionable or biased texts, and the habit of making grossly false statements of fact in persuasive-sounding language.
In order to remedy these shortcomings, OpenAI added a fundamentally new dimension to the training concept for its next language models InstructGPT and ChatGPT : Instead of leaving a model alone with huge amounts of text from the Internet, it was subsequently taught by human “teachers”, concrete ones To follow the instructions of the users and to make statements that are ethically justifiable and correct in terms of content. In order to ensure the effectiveness of this training, the algorithmic approach of the pure transformer model had to be expanded by a further step – the so-called reinforcement learning.
The impressive achievements of ChatGPT are the result of a whole range of different algorithms and methods as well as many tricks, some of which are very small. In this article, the focus is on providing an intuitive basic understanding of the technology without getting bogged down in too many mathematical or technical details. The links in the text refer to sources that fill in the gaps in this presentation.
