फंगल कंप्यूटर्स: कैसे मशरूम न्यूरोमोर्फिक चिप्स को शक्ति प्रदान करते हैं

जैविक कंप्यूटर का एक नया प्रकार

Computing was initially developed with analog technology, which differs from digital technology in that it uses more complex (and messy) signals instead of clearly distinct 1 & 0.

स्रोत: Unison Audio

सामान्य तौर पर, डिजिटल सिग्नल का विश्लेषण, प्रतिकृति और प्रसारण आसान होता है। लेकिन एनालॉग सिग्नल वास्तविक दुनिया की जटिलताओं को अधिक सूक्ष्मता से संभाल सकता है।

इसी कारण वैज्ञानिक नई AI, सेंसरिंग और अन्य अनुप्रयोगों के लिए एनालॉग कंप्यूटिंग की ओर फिर से देख रहे हैं। इसमें कई विभिन्न डिज़ाइन वाले तथाकथित न्यूरोमोर्फिक चिप्स शामिल हैं, जो मस्तिष्क के डेटा प्रोसेसिंग तरीके की नकल करते हैं।

मस्तिष्क जैसी क्षमता का उपयोग करके कंप्यूटिंग करने की नई दिशा में जैविक कंप्यूटर का उदय हुआ है, जहाँ ऑर्गेनिक टिश्यू सिलिकॉन चिप्स के बजाय कार्य करते हैं। एक उदाहरण है ऑर्गेनॉइड्स, मानव न्यूरॉन्स से निर्मित लैब‑ग्रो टिश्यू, जो कंप्यूटिंग कार्य कर सकते हैं। इनके साथ कार्यात्मक मस्तिष्क टिश्यू की 3D प्रिंटिंग की नई तकनीकें मिलकर पूरी तरह नई, अजीब प्रकार की कंप्यूटिंग क्षमताओं का मार्ग खोल सकती हैं।

एक और प्रकार के इलेक्ट्रॉनिक घटक जो जैविक घटकों का उपयोग करते हैं, उन्हें सूची में जोड़ना चाहिए, जहाँ ओहायो स्टेट यूनिवर्सिटी के वैज्ञानिकों ने न्यूरोमोर्फिक ऑर्गेनिक मेम्रिस्टर्स बनाए, जो पिछले विद्युत स्थितियों को याद रख सकते हैं। हालाँकि उन्होंने इसे न्यूरॉन्स से नहीं, बल्कि मशरूम से बनाया।

They published their discovery in the scientific review PLOS One, under the title “Sustainable memristors from shiitake mycelium for high-frequency bioelectronics.”

न्यूरोमोर्फिक कंप्यूटिंग का उपयोग क्यों करें?

NPUs का उदय

Neural Processing Units (NPUs), also called neuromorphic chips, are a type of AI hardware that present a few advantages compared to more traditional chips like CPUs and GPUs:

• अधिक लचीला डिज़ाइन, जिससे चिप आर्किटेक्चर को प्रशिक्षण डेटा के अनुसार अनुकूलित किया जा सकता है।
• बहुत कम ऊर्जा खपत, कभी‑कभी समान GPU की तुलना में केवल 1/100^th तक।
• कम गर्मी उत्पन्न होना, जिससे उन्नत AI डेटा सेंटरों में कूलिंग की समस्या कम होती है।

(You can read more about AI-specialized hardware, including NPUs, in our dedicated report.)

“माइक्रोचिप्स को विकसित करने में सक्षम होना जो वास्तविक न्यूरल गतिविधि की नकल करते हैं, इसका मतलब है कि स्टैंडबाय या जब मशीन उपयोग में नहीं है, तब बहुत कम पावर की आवश्यकता होगी।

यह एक बड़ा संभावित कम्प्यूटेशनल और आर्थिक लाभ हो सकता है।”

John LaRocco – Ohio State’s College of Medicine में सायकेट्री के शोध वैज्ञानिक।

Many methods are currently being explored for creating neuromorphic chips:

• Leverage incipient ferroelectricity, a still poorly understood phenomenon.
• Active substrate using vanadium or titanium.
• Using memristors, a new type of electronic component, which can perform AI tasks at 1/800^thof the normal power consumption.

मेम्रिस्टर्स कैसे सिनैप्स की नकल करते हैं

Memristors are electronic components that mimic neuron-connecting synapses by remembering which electric state they were toggled to after their power is turned off.

This can greatly reduce the energy and time lost from shuttling data back and forth between processors and memory.

One of the key strengths of memristors is their capacity for efficient and self-adaptive in situ learning, which is critical for applications in robotics and autonomous vehicles.

Moreover, the low power consumption of memristors is particularly beneficial in robotics and autonomous vehicles, where energy efficiency is paramount. Hybrid analog–digital memristor systems can minimize power usage during processing without sacrificing responsiveness.

The problem so far is that creating electronic memristors has relied on emerging technologies with low production yields and unreliable electronic performance, due to how recent this technology is.

Using actual neurons, like with organoids, is also an option, but neurons are actually very difficult cells to work with, being relatively fragile and hard to grow.

But neurons are not the only biological tissues capable of processing and responding to electrical signals.

One potential alternative is mycelium, the tissue constituting ordinary mushrooms, a type of organism known for its remarkable sturdiness. They can be grown with simpler bioreactors and nutrient cultures than those required for conventional neurons and neural organoids.

मशरूम कंप्यूटर्स बनाना?

Fungal materials display conductive pathways that can form dynamically under the influence of electrical stimuli, similar to the conductive filaments formed in conventional memristors.

This adaptability can lead to enhanced performance in neuromorphic applications through the facilitation of variable resistance states that mimic synaptic behaviors more closely than traditional memristive materials.

Organic materials also have the advantage of operating effectively at lower voltages while maintaining the stable switching characteristics important for memristors, even lower than for electronics memristors, themselves much less energy-consuming than traditional computing components.

This could be important for energy-efficient devices for portable electronics and Internet of Things applications that might rely on a very low energy supply.
स्क्रॉल करने के लिए स्वाइप करें →

भोजन योग्य मशरूम कंप्यूटिंग के लिए क्यों काम करते हैं

The researchers used common button mushrooms, as well as edible and medicinal Shiitake mushrooms for their experiments, both species whose cultivation is well understood and cheap.

Shiitake mushrooms have previously been shown to possess a porous carbon structure when activated. This porous structure can enhance the electrochemical performance of devices, making them suitable candidates for use in energy storage systems, including supercapacitors and, potentially, memristors.

They are also very radiation-resistant, which could help for applications like aerospace, where electronic chips can be damaged by ionizing radiation like UV and solar winds.

फंगल इलेक्ट्रिकल रिस्पॉन्स

The scientists connected the test fungal mass after it was dehydrated.

स्रोत: PLOS One

They were then tested across a range of voltages, waveforms, and frequencies for their potential memristor capabilities.

The responding analog signal was displaying strong memristive characteristics, mimicking in analog the digital signal.

स्रोत: PLOS One

Overall, the observed rapid switching speed of 5,850 Hz, an accuracy of 90% (± 1%), relatively low energy consumption, light weight, and radiation resistance all appear to make fungal memristors attractive for edge computing, aerospace, and embedded firmware applications.

However, accuracy decreased as the frequency increased, so not all types of signals could likely be processed/computed with that method.

It should also be noted that the method creates only biodegradable materials (food-grade shiitake is grown on wood chips) and requires no rare earth or toxic materials, contrary to conventional electronic chips.

भविष्य की संभावनाएँ

The study here was a first trial, and was limited in two ways:

• The tests were relatively short, running over only 2 months. So the long-term capacity of the fungal memristors still needs to be investigated.
• The method used a bulk production, while actual applications would need a microculture of the mycelium grown in a dedicated environment, providing much smaller and much more controlled results.

So this is really just a proof of concept, a demonstration that something as exotic as fungal computing is even possible and reliable.

Any future design would likely see the use of more consistent cultivation techniques using 3D-printed templates and structures that shape the shiitake mushroom into the desired geometry.

Programming could also be facilitated by adding electrical contacts to a 3D-printed cultivation structure.

Finally, long-term use would necessitate preservation, which could involve a variety of techniques, including dehydration, desiccation, freeze-drying, certain hydrogels, and special coatings.

Still, the idea of developing memristors with exclusively organic materials, and resistant, cheap, and biodegradable mushroom material at that, is intriguing.

बायोप्रिंटिंग में निवेश

BICO Group AB (BICO.ST)

As organic-based computing progresses, 3D printing of living tissues will likely become an increasingly used tool. First in research, and then for the actual production of devices leveraging this technology.

One leader in the field has been Cellink, whose machines are used for bioprinting by researchers all over the world.

स्रोत: Cellink

In 2021, Cellink was renamed as the BICO Group, following its acquisition of Cytena in 2019 and Scienion in 2020.

Cellink is still the brand name for the bioprinting part of the business. This could also be used for creating on-demand 3D tissues or organs. (You can read a discussion on this topic in “3D Printing Human Organs – How Realistic Is It?”).

Bioprinting represents around 1/5^th of the business, with the bioscience automation segment, including imaging of biological samples, making more than 3/5^th of revenues.

स्रोत: BICO Group AB

In the long run, bioprinting companies are likely to evolve from providing tools to researchers to becoming suppliers of pharmaceutical companies’ bioprinting therapies for patients.

This will, in turn, completely change the number of bioprinters in use and, more importantly, the volume of consumables sold every month.

This is the same process that occurred for other biolab equipment manufacturers, including genome sequencing machines from PacBio (PACB) and Illumina (ILMN), which end up making 80% of their revenues from recurring sales of consumables.

As the BICO Group is not solely dependent on this field, it can keep improving the technology until it reaches a critical mass of users, while also making money and building its sales network with bioresearchers from its other, more mature products in bioscience automation.