“75% of all plastic used is made of really thin alternating layers: hard, soft, hard, soft, and so on. We’ve known since the 1950s that the soft stuff is holding the hard stuff together.
What we show in the new study is how easily those soft connectors break even under quiescent conditions such as in a landfill. Once that layer fails, the hard segments have nowhere to go — they scatter into the environment.Why is that a problem?
These pieces float around, and some end up in human bodies. The smallest pieces pass through cells and into the nucleus, where they can start messing with DNA. Nano- and microplastics, which seem to have similar sizes and shapes to asbestos, raise the potential that they could cause cancer, heart disease/stroke, and other diseases.”
MIT Technology Review’s Will Douglas Heaven provides a comprehensive overview of the AI revolution in software development, showcasing the innovative startups driving this change.
They are monetizing a real need for programmers and businesses, who are already using these tools massively. A quarter of the code produced by Google today is generated by AI, according to Google CEO Sunday Pichai.
The key takeaway is that these programs are so good that the job of engineers is now to write prompts and review code written by machines.
The first step has been to train the models from billions of lines of code found online, offering a super-powerful autocorrect.
They are now using machine learning techniques to allow the model to “play” in a simulated environment iteratively, much like Google’s DeepMind did with AlphaGo, when it won against the world champion in 2017.
The goal of the game is to arrive at a model that understands the logic underlying any programming language.
Achieving that logical understanding would be to software development what the introduction of ATMs has been to banking.
The speed of development once this logical understanding is achieved will allow the machines to solve problems by programming on the fly, and this they say will be the true AGI.
. First interactive CAD system (right), DAC-1, circa 1959. (Source: IBM)
A super interesting eBook from consulting firm Jon Peddie Research that traces the long history of CAD technology development, right up to today’s systems.
“The computer-aided design industry has undergone significant transformations since its emergence in the late 1950s and early 1960s. The advent of CAD in the 1960s ushered in an era of automation up to the ’80s that persists today. However, CAD is now just one element within a progressively intricate system tied to the real and virtual worlds.”
Plastic pollution is a global crisis that is harming the environment and human health. There is an urgent need to take action to reduce plastic pollution, and one of the most promising approaches is to develop a global plastics treaty.
While the so-called High Ambition Coalition to End Plastic Pollution — which includes the EU, Canada, Japan and Australia — called in Nairobi for curbs on plastic production (1), a newly formed Global Coalition for Plastics Sustainability, including Saudi Arabia, Russia, Iran and China, rejected production limits and emphasised recycling instead (2).
Environmental health lawyer Vito Buonsante argues that the priority has to be reducing the production of plastics and making them less toxic, emphasizing that no plastics are known to be safe and circular (3).
Whether or not production limits will ultimately be included in the global plastics treaty remains to be seen, but Rebecca Marmot, chief sustainability officer at consumer goods company Unilever, believes that, by setting binding global rules, the treaty has the potential to reshape the world’s relationship with plastic, accelerate the transition towards a circular economy, and end plastic pollution (4).
Unilever, along with Nestlé and dozens of other big consumer brands, is a member of the Business Coalition for a Global Plastics Treaty, a grouping convened by the Ellen MacArthur Foundation and wildlife campaign group WWF (5). Its vision is a circular economy in which plastic never becomes waste or pollution, and the value of products and materials is retained in the economy (6).
This entails reduction of plastic production and use and, whenever possible, moving away from single-use plastics in favour of reusable and more durable solutions (7). Applied widely enough, such policies could reduce annual volumes of plastic pollution by at least 80 per cent by 2040 compared to business-as-usual, and achieve near-zero plastic pollution by 2060 globally (8).
Nestlé is carrying out 20 pilots in 12 countries for different reuse and refill business models, according to Nestlé’s Sustainability Head Katherine Roussell (9). However, she stresses that a wider transition will need regulation and industry-wide collaboration (10).
“Reuse and refill requires a system shift and multiple actors need to add different elements to their business models,” Roussell says (11). “If one can dream a dream, certain approaches to rolling out reuse would be included in the treaty — to create standardisation, cost savings and simplicity” (12).
Consumers, too, will need to learn new habits (13). “We need to incentivise behaviour change and create compelling user experiences and value propositions because, today, refill and reuse are less convenient for the consumer,” Roussell says (14). She cites a Nestlé study which showed that, in the UK, only people without children are using reuse and refill in significant ways (15).
Carsten Wachholz, global plastics treaty co-lead at the Ellen MacArthur Foundation, agrees that systemic change is needed — and soon (16).
“We must change how we design and use plastics as we cannot simply recycle or reduce our way out of this crisis,” he says (17). “Now is the time for tougher policy and accelerated business action” (18).
References
High Ambition Coalition to End Plastic Pollution. (2022, May 30). Urgent action needed to curb plastic production and consumption. [Press release].
Global Coalition for Plastics Sustainability. (2022, June 15). Statement on the global plastics crisis. [Press release].
Buonsante, V. (2022, June 20). A global plastics treaty must address production and toxicity. Environmental Health News.
Marmot, R. (2022, September 28). A global plastics treaty: Our chance to reshape our relationship with plastic. The Guardian.
Business Coalition for a Global Plastics Treaty. (n.d.). About us.
Ellen MacArthur Foundation. (2022, September 28). A new normal for plastics.
Business Coalition for a Global Plastics Treaty. (2022, June 14). A circular economy for plastics.
Business Coalition for a Global Plastics Treaty. (2022, June 14). A circular economy for plastics.
Roussell, K. (2022, October 4). Nestlé’s journey towards a circular plastics economy. Circular Economy Forum 2023.
Roussell, K. (2022, October 4). Nestlé’s journey towards a circular plastics economy. Circular Economy Forum 2023.
Roussell, K. (2022, October 4). Nestlé’s journey towards a circular plastics economy. Circular Economy Forum 2023.
Roussell, K. (2022, October 4). Nestlé’s journey towards a circular plastics economy. Circular
The quest for novel materials has always been at the heart of technological advancement, driving innovations across countless industries. Now, a groundbreaking deep learning tool developed by Google AI, dubbed GNoME (Graph Networks for Materials Exploration), is poised to revolutionize this pursuit, ushering in an unprecedented era of discovery.
At its core, GNoME leverages the power of graph networks, a specialized form of artificial intelligence adept at learning from data structured as graphs. This makes it uniquely suited for the intricate world of materials science, where atomic structures and their interconnections can be naturally represented as graphical relationships.
GNoME operates by meticulously analyzing a vast database of existing materials. This comprehensive dataset encompasses crucial information such as crystal structures, chemical compositions, and energy states.
By discerning complex patterns and relationships within this known data, GNoME gains the ability to accurately predict the properties of entirely new, hypothetical materials.
The impact of GNoME’s initial explorations has been nothing short of astounding. The tool has already identified an astonishing 2.2 million new materials.Critically, a significant subset of these – approximately 380,000 – are predicted to be stable. This stability prediction is paramount, indicating that these materials are likely to exist in nature and possess the potential for real-world applications, paving the way for transformative technological breakthroughs.
The potential applications of GNoME’s discoveries span a wide and diverse range of industries:
Electronics:GNoME could unlock the secrets to next-generation electronic components, from high-performance superconductors to more efficient semiconductors, paving the way for faster and more powerful devices.
Energy:The tool holds immense promise for advancing clean energy solutions, facilitating the discovery of superior materials for highly efficient solar cells, longer-lasting batteries, and other crucial energy storage devices.
Medicine: In the realm of healthcare, GNoME could accelerate drug discovery by identifying novel materials for pharmaceutical applications and lead to the creation of more advanced and effective medical devices.
The implications for everyday life are equally profound. The new materials unearthed by GNoME could directly translate into a host of enhanced consumer products:
Smartphones and Laptops: Imagine smartphones with vastly extended battery life and more powerful processors, or laptops that are significantly lighter and more durable. GNoME’s materials could make these advancements a reality.
Electric Vehicles: The development of more efficient and affordable electric cars could be greatly accelerated by the discovery of new materials that enhance battery performance and vehicle construction.
Solar Panels and Batteries: Expect to see substantial improvements in the efficiency of solar panels and the longevity and power of batteries, contributing to a more sustainable and electrified future.
In essence, GNoME represents a monumental leap forward in materials science. By dramatically accelerating the pace of discovery, this innovative tool has the potential to unlock a future teeming with novel technologies and improved products, profoundly impacting our lives for the better. The era of targeted, intelligent materials discovery has truly arrived.
“A revolutionary chatbot technology that uses natural language processing and machine learning to create engaging and intelligent conversations with users. Developed by OpenAI, ChatGPT is designed to provide users with personalized and interactive experiences that feel like chatting with a real person.”
As a technology enthusiast, I am constantly on the lookout for new and innovative tools that can make my life easier and more efficient. And when it comes to answering complex questions, I have found that ChatGPT is a game-changer.
This revolutionary tool uses advanced natural language processing and machine learning algorithms to provide accurate and detailed answers to even the most complex questions. Whether you’re a student trying to ace your exams, a professional looking to gain a competitive edge, or simply someone who loves to learn and explore new ideas, ChatGPT is an invaluable resource.
One of the things that sets ChatGPT apart from other question-answering tools is its ability to understand and interpret context. It can quickly and accurately identify the key concepts and themes within a question, and then provide detailed and comprehensive answers that are tailored to your specific needs.
Whether you’re looking for information on a particular topic, trying to solve a difficult problem, or simply want to learn more about a particular subject, ChatGPT is there to help. Its intuitive interface makes it easy to use, and you can ask it questions in natural language, just as you would a human expert.
In addition to its impressive ability to answer complex questions, ChatGPT also has a wealth of knowledge at its disposal. It can provide information on a wide range of topics, from science and technology to history and culture. This means that you can use ChatGPT as a comprehensive reference tool, no matter what your interests or needs may be.
Overall, I am incredibly impressed with ChatGPT and its ability to answer complex questions. Its advanced technology and extensive knowledge base make it a valuable resource for anyone who wants to learn more, solve problems, and stay on top of the latest developments in their field. I highly recommend giving it a try!
The previous text was completely generated by Chat GPT, after my input: “Can you write an enthusiastic blog post on ChatGPT ability to answer complex questions?”
To test its capabilities in a field in which I have some expertise, I asked “Can you write a list of best practices in consumer product concept development?”, the answer has been:
Identify the target market and their needs and preferences.
Conduct market research to understand the competitive landscape and identify potential gaps in the market.
Develop a unique value proposition for the product.
Create a detailed product concept and specifications.
Test the product concept with a focus group or other market research methods to gather feedback.
Develop a detailed product development plan with timelines and budgets.
Collaborate with design and engineering teams to create prototypes and test for functionality and user experience.
Continuously gather feedback and make adjustments to the product concept as needed.
Develop a comprehensive marketing and sales plan to launch and promote the product.
Monitor market trends and customer feedback to ensure the product continues to meet customer needs and remain competitive.
It didn’t go into much detail, but consider you can expand a topic and ask a new question, and the bot will go deeper in the rabbit hole apparently without limits!
It feels like googling without having to click on each link while sorting a ton of noise to get the information you are looking for. This could be connected to larger data sets, to find information without effort. Now we need to ask the right questions.
Look at the sofas that came up from the application of PU foam in the 60’s, it was almost as if the PU foam was asking to be modeled in this shape. Look at the styles that came up from architects that were exploiting concrete to its limit: they came up with Brutalism. Look at the peculiar style that emerged from blacksmiths in the 1800s. They had a limited number of operations to model metal rods, and that operations forged the style.
Look at the tools which are used now and you will have a spectrum of styles.
So, if there is a limited dialogue between the mesh based tools and CAD used to manufacture physical goods, you will have more expressions influenced by CAD.
Now we can manufacture potentially any shape with the available manufacturing technology, and a lot of shapes are still lofts and cut extrudes. This could be remembered as the golden age of CAD in Industrial design, producing many great products with this peculiar style guided by parametric functions.
Mercedes-AMG GT R Roadster entirely made in Blender by Nahid Mustafazade on Artstation
Polygonal modeling is the most widespread and versatile 3D modeling technique. The expressive potential and usability of this technique should be a must have for industrial designers. But we are far from using its full potential.
Meshes can describe any 3D shape, with a level of precision that depends on the number of polygons. Game assets are optimized to save computing resources. Based on Subdivision surfaces, while working on a few polygons, they describe complex and polished surfaces. In this conceptually simple way, artists can create complex and amazing shapes, in an easy way. So why aren’t we seeing it everywhere on the industrial design 3d modeling pipeline?
The standard in industrial design is modeling with Parametric surfaces, which I call NURBS. It’s the surface-generating “language” on which Rhinoceros 3D is based, ideal for modeling automotive-style, aerodynamic shapes. The precision and control you get with parametric surfaces are much higher, but I think that large organisations continue to use the same software that their employees already master (it is a legacy system) and resist change.
The problem
The shapes that come up quite easily with subdivision surfaces require much more effort to be made with paramedic surfaces. It’s not a lack of imagination, will or ability from designers. It’s as if the program decides what you can and cannot do, while outside the industrial design world, professionals continue to produce great models and renders at a impressive rate, thanks to software like Zbrush, Maya, Blender, Max, with the tools and user interface which are 20 years head start.
While prominent design firms keep using cut extrudes and lofts, with good looking rounded edges, game design is experiencing the equivalent of the renaissance in terms of style and new ideas.
How is it possible that the complexity of the shapes in products is so basic? Is it just because everyone follows Dieter Rams teachings? Why everything seems copied from Apple products? I’m saying that it’s not just fashion, it’s lack of tools.
T-splines tried to bridge this gap by offering a plugin for Rhino, recently integrated in Autodesk Fusion360, while Creo Parametric offers freestyle, a great way to import and edit a lo-poly mesh into a parametric software. Until now, these programs had a limited number of functions, and it seems hard to catch up with the mesh modeling interface.
The picture above shows the underlying mesh of a simple shape, with Semi-Sharp Creases on the edges
I think industrial designers should integrate organic modeling features alongside the classic parametric tool. Not just to “explore” new shapes, as advertised by some software houses, even though that is a great step forward.
Subdivision surfaces and the advanced modeling interface you see in Zbrush and Blender should be merged seamlessly into the industrial design workflow, because the advantage to create gorgeous shapes is great, and most of all, it shouldn’t be painful.
Working for the toy industry in the last 4 years I sculpted meshes on Zbrush and imported the obj on my favorite parametric softwares. Could Rhino 7 solve the problem? It seems to deliver quite well, so far.
I needed an email alert to know when a new shopper would became available on the groceries website.
During the pandemic, Supermercato24 was my favorite food delivery service, it offers to bring the groceries at home, managing the shoppers that go to the supermarket.
Unfortunately, as everyone is forced to stay at home, shoppers remain available only for a few minutes before being all reserved. It’s hard to find the right spot if you want your food delivered in a few hours or even the next day.
I thought of hiring a programmer on Upwork, to create a web based script that would help me with this problem. The script needed to log on the website for me and send an alert via email when new shoppers would be available again. In that way I should be able to rush on the website and place an order.
“Upwork is a global freelancing platform where businesses and independent professionals connect and collaborate remotely” (wikipedia).
So I placed the title of the job posting, trying to be very specific, as the more precise you are, the least problems of understanding are going to show up later.
Than I set up the required skills, in my case a programmer able to do automation.
Finally I published the job posting. And that’s when the fun part started: in minutes I received a job application from Ait Doukali Z., a programmer from Morocco.
It’s been really a pleasure working with him, as he’s an expert programmer and quickly created a program in python on his computer, sending the first test emails. Later he placed it on a Google Cloud virtual machine. The next day it needed only some minor changes, and today I was receiving emails as expected.
So, I discovered that if you want the shopper available for the next few hours you need a bot like this to catch it, because new shoppers show up in a totally unpredictable way.
Now I can have a shopper in 3 hours at my door.
Final notes:
In 2015 I worked on Upwork as 3D model maker and industrial designer and it’s been a really intense and rewarding experience.
I felt empowered as my clients were piling up at a fast pace; I was plenty of good ratings from my clients. Corporate employees in need of an extra hand for a project, more often makers searching for a personalized service to realize their projects, sometimes startups with a new product, or inventors with an idea that needed to be designed, 3D modeled, prototyped to show it to potential clients.
The so called “gig economy” is one of those phenomena ignited by the internet where the tension between low prices for consumers and fair job conditions for the workers started to heat up a few years ago; now you can’t feel at ease without taking the side of the liberal economy OR the workers rights, but for now I wanted to focus on creating a cloud based script in two days. I posted a fixed price job at 30€ for the whole project, and I received an offer probably because the worker was at the beginning of its career on the website, he needed to build his reputation. Probably in the future, as the worked hours will be higher and the ratings too, he will only accept payments by the hour, realistically at 30€/hour. I placed a tip of 20€, feeling a bit guilty.
The online jobs marketplace is a great resource for freelancers. During my experience as a 3D model maker and designer in Italy I often struggled with a system where new contractors are found by word of mouth. Companies can’t trust a freelancer if it’s not recommended, or if they can’t count on trust built in years of collaboration. But in a marketplace you can trust the rating of a worker, in a similar way to the rating you trust for a product on Amazon.
I just suggested that people can be treated as goods, entering in the muddy waters of mercification of the workers, but I still see a jobs marketplace as powerful tool for a freelancer.
And I didn’t yet mentioned the unique possibility offered on Upwork, to have automatically enforced contracts and payments, something you can only dream of if you are a freelancer in Italy (think of 60 days payment terms, if only the company is still alive by that time).
The freelancers rating system is a central part of the trust that clients can put in a freelancer and indispensable to expect the desired outcome.
For a freelancer on a marketplace, rating is the most important presentation, even more important than the price they offer.
For small companies and private clients, this service can unlock the potential of a global market of really skilled workers that offer specialized services at a fraction of the price that a large studio can offer, unlocking the possibilities for great ideas to be realized.
