However, despite their remarkable performance advantages, composite materials are not without drawbacks. Their primary weakness lies in their layered structure. Unlike aluminum, which can absorb relatively large impacts without catastrophic failure, composites are vulnerable to delamination. Small impacts, which might only dent an aluminum panel, can cause the thin, bonded layers of composite plies to separate or crack. This phenomenon has long been considered the “Achilles’ heel” of composite technology and represents a key challenge for aerospace engineers seeking to maximize both safety and performance.

A research team at the Massachusetts Institute of Technology (MIT) has recently introduced a promising solution to this problem. By innovatively reinforcing the bond between composite layers, they have succeeded in creating materials that are significantly stronger and more resistant to damage than conventional composites. Their findings, published in the journal Composites Science and Technology, highlight the use of carbon nanotubes—extraordinarily strong, nanoscale rolls of carbon atoms—as a structural reinforcement within the composite matrix.

The MIT team, led by postdoctoral researcher Roberto Guzman (now at the IMDEA Materials Institute in Spain) and supervised by Professor Brian Wardle of MIT’s Department of Aeronautics and Astronautics (AeroAstro), embedded forests of vertically aligned carbon nanotubes within the polymer glue that holds carbon fiber plies together. These nanotube “forests” act as nanoscale stitches, penetrating into the tiny crevices of each layer and serving as a scaffold that firmly locks the layers together. Unlike previous reinforcement techniques such as Z-pinning or 3D weaving—which involve inserting relatively large fiber bundles through the plies and often damage the surrounding material—the carbon nanotubes are so small that they do not disrupt the structural integrity of the carbon fibers.

Experimental testing confirmed the effectiveness of this approach. In a tension-bearing test, in which a bolt was inserted through the material and then subjected to pulling forces, the nanotube-stitched composites withstood 30 percent more force than conventional composites before failing. Similarly, in an open-hole compression test, where force is applied to compress the area surrounding a bolt hole, the new composites endured 14 percent more force before cracking. These results indicate a substantial improvement in both tension and compression resistance—two critical performance parameters for aircraft structures.

Professor Wardle explains why this nanoscale solution is so effective: “Size matters. Traditional stitching or pinning techniques introduce reinforcements thousands of times larger than the carbon fibers themselves, causing considerable damage in the process. By contrast, carbon nanotubes are just 10 nanometers in diameter—nearly a million times smaller than carbon fibers—so they integrate seamlessly. Additionally, nanotubes have about a thousand times more surface area than carbon fibers, which greatly enhances their bonding with the polymer matrix.”

The implications of this work extend far beyond the laboratory. Today’s most advanced airliners, such as the Boeing 787 Dreamliner and the Airbus A350, already incorporate over 50 percent composite materials by weight. By improving the strength, durability, and damage tolerance of these composites, the MIT technique could make future aircraft both lighter and safer. In practical terms, it could allow for the design of thinner, lighter structural components that still meet rigorous safety requirements. This means additional weight reduction, more efficient use of fuel, and fewer carbon emissions over the lifespan of each aircraft.

Moreover, the innovation has specific potential in areas where composites are most vulnerable—such as around holes and fasteners. Conventional composites often crack around bolted joints, but the enhanced material developed by the MIT team shows far greater resilience in these critical regions. This could extend the service life of components, reduce maintenance costs, and further increase the economic benefits of composite-heavy aircraft designs.

Roberto Guzman emphasizes the broader impact of their research: “More work needs to be done, but we are optimistic that this technology will lead to stronger, lighter aircraft structures. That translates into enormous amounts of fuel saved, which is not only good for the environment but also for airline operating costs.”

In collaboration with Saab AB, a leading aerospace and defense company in Sweden, the MIT researchers are continuing to explore ways to scale up this technology for industrial applications. If successfully implemented, the carbon nanotube stitching approach could mark a major leap forward in the evolution of aerospace materials—paving the way for the next generation of safer, greener, and more efficient aircraft.

Journal Reference:

R. Guzman de Villoria, P. Hallander, L. Ydrefors, P. Nordin, B.L. Wardle. In-plane strength enhancement of laminated composites via aligned carbon nanotube interlaminar reinforcement. Composites Science and Technology, 2016; 133: 33 DOI: 10.1016/j.compscitech.2016.07.006

The announcement has sparked considerable interest in both academic and commercial circles, as Safe Superintelligence is emerging as a prime example of how cutting‐edge artificial intelligence research can rapidly translate into substantial market value. Despite the fact that the company has not yet generated any revenue, the elevated valuation reflects investor expectations regarding the transformative impact that its innovations might have on various sectors. With $1 billion already raised from prominent investors such as Sequoia Capital, Andreessen Horowitz, and DST Global, the startup appears to be positioned at the nexus of high-stakes technological advancement and strategic financial investment.

The extraordinary trajectory of Safe Superintelligence can be attributed, in large part, to the pedigree of its founding team. Ilya Sutskever, whose contributions at OpenAI played an instrumental role in shaping the technological underpinnings of groundbreaking systems like ChatGPT, is widely regarded as one of the foremost authorities in artificial intelligence. His reputation in the AI community is further bolstered by his previous achievements and the visionary research that has set new paradigms in machine learning and neural network architectures. Alongside Sutskever, the company’s founding team includes former OpenAI researcher Daniel Levy and Daniel Gross, the ex-lead of Apple’s AI projects. The collective expertise of these individuals offers a formidable blend of theoretical insight and practical know-how, which has, in turn, helped to galvanize investor confidence.

The current funding discussions, which suggest a valuation of “at least” $20 billion, signal a transformative moment not only for Safe Superintelligence but also for the broader field of AI-driven enterprises. The valuation leap from $5 billion to $20 billion within a span of a few months is unprecedented in many respects and is indicative of a rapidly changing landscape in which traditional revenue metrics are being re-evaluated in light of potential future impact. Such an increase reflects the belief that the company’s research and development efforts could pave the way for revolutionary applications across diverse industries—from healthcare and finance to transportation and national security.

At the heart of this dramatic valuation surge is the concept of “safe” artificial intelligence. While the term “superintelligence” might evoke images of futuristic scenarios where machines surpass human capabilities, Safe Superintelligence is dedicated to ensuring that as AI systems become more advanced, they are developed in ways that prioritize safety, ethics, and long-term societal benefit. The company’s focus on these critical dimensions is reflective of an emerging consensus among leading AI researchers: that robust safety protocols must be integrated into the development of increasingly powerful algorithms and autonomous systems. This approach not only addresses the technical challenges associated with AI advancement but also seeks to mitigate potential risks, thereby fostering an environment where innovation can proceed without compromising fundamental ethical standards.

The substantial valuation of Safe Superintelligence can be interpreted as a manifestation of broader market trends that prioritize long-term potential over immediate profitability. In an industry where breakthrough technologies are often in a pre-revenue stage, traditional financial metrics are giving way to assessments of intellectual capital, research potential, and strategic influence. The willingness of investors to commit significant capital to a company that has yet to demonstrate revenue generation is indicative of a paradigm shift in investment strategies, one that values the possibility of paradigm-changing discoveries over short-term financial returns. This shift is particularly pronounced in the AI sector, where rapid technological progress and disruptive potential are the norm rather than the exception.

Furthermore, the impressive roster of investors backing Safe Superintelligence adds another layer of credibility to the company’s ambitious valuation. Firms such as Sequoia Capital, Andreessen Horowitz, and DST Global have a long history of identifying and nurturing groundbreaking technologies. Their involvement in the current funding round not only provides substantial financial backing but also serves as an endorsement of the company’s strategic vision and its capacity to achieve long-term success. In many ways, the investment community’s support for Safe Superintelligence exemplifies the growing recognition that artificial intelligence will continue to be a major driver of economic growth and technological innovation in the coming decades.

The emergence of Safe Superintelligence as a major player in the AI landscape also prompts a broader discussion about the evolution of startup valuation methodologies. Historically, companies in the technology sector were often valued based on tangible revenue figures, market share, and profitability metrics. However, as the boundaries between research, development, and commercial application blur, investors are increasingly focusing on a company’s intellectual property, its technical expertise, and its potential to influence entire industries. In the case of Safe Superintelligence, the leap in valuation reflects a belief that the company’s contributions could lead to fundamental shifts in how artificial intelligence is integrated into everyday life. This reorientation of value assessment is emblematic of a broader trend in the tech industry, where disruptive innovations are often valued based on their capacity to generate long-term societal and economic impact, rather than their immediate financial performance.

The strategic implications of such a high valuation are manifold. For one, the infusion of new capital at this level is likely to accelerate the company’s research and development activities, enabling it to attract top-tier talent, invest in state-of-the-art infrastructure, and pursue ambitious projects that could redefine the limits of current AI technology. Moreover, the heightened valuation serves as a powerful signal to the market, potentially attracting further interest from both private and institutional investors. As a result, Safe Superintelligence may find itself at the center of a virtuous cycle in which increased funding begets accelerated innovation, which in turn drives further investment and elevates the company’s strategic positioning within the competitive landscape.

At the same time, the company’s meteoric rise in valuation raises important questions about the sustainability of such high market expectations. The fact that Safe Superintelligence has yet to generate revenue underscores the inherent risks associated with investing in early-stage, high-potential ventures. While the current enthusiasm among investors is fueled by the promise of transformative breakthroughs, it also necessitates a rigorous and transparent evaluation of the company’s technological roadmap and its capacity to translate research excellence into commercial viability. In this context, the role of strategic management becomes paramount. Ensuring that the company’s growth trajectory aligns with both market expectations and responsible innovation practices will be critical in maintaining investor confidence and achieving long-term success.

The debate surrounding the future impact of Safe Superintelligence is not confined to financial circles alone; it also extends to the academic and scientific communities. Scholars and researchers are increasingly interested in the ethical and practical dimensions of developing “safe” AI systems, particularly in light of growing concerns about the potential risks associated with unbridled technological advancement. By prioritizing safety and ethical considerations, Safe Superintelligence is positioning itself at the forefront of a movement that seeks to balance rapid innovation with responsible stewardship. This approach has the potential to influence not only the trajectory of the company but also the broader discourse on how artificial intelligence should be developed and regulated in the future.

Moreover, the high-profile nature of the startup’s leadership further enhances its ability to shape industry standards and academic debates. Ilya Sutskever’s illustrious career, marked by significant contributions to the field of machine learning and neural networks, lends a level of credibility and gravitas to the company’s endeavors that few other startups can match. His involvement is likely to attract further interest from academic institutions, research labs, and policy think tanks, all of which are keen to explore the interplay between cutting-edge AI research and real-world applications. In this sense, Safe Superintelligence is not merely a commercial enterprise; it is also a catalyst for broader intellectual engagement, one that is poised to stimulate new ideas and foster cross-disciplinary collaborations.

The multifaceted nature of the current funding discussions around Safe Superintelligence also invites a consideration of the broader geopolitical and economic implications of AI innovation. As countries around the world vie for leadership in the AI domain, the ability of startups like Safe Superintelligence to secure substantial funding and achieve high valuations is indicative of a shifting global balance of technological power. The strategic investments made by leading venture capital firms are not only a bet on the company’s future success but also a reflection of broader trends in the international race for AI supremacy. In this context, the company’s focus on safe and responsible AI development may serve as a model for how technological progress can be aligned with ethical imperatives, thereby contributing to a more sustainable and inclusive future.

The confluence of visionary leadership, robust investor support, and an ambitious technological agenda makes the current funding round for Safe Superintelligence a subject of considerable academic and practical interest. It challenges conventional paradigms of startup valuation and invites a re-examination of the metrics by which technological innovation is assessed. The company’s journey from a pre-revenue startup to a high-valuation enterprise within a short span of time exemplifies the transformative potential of artificial intelligence and underscores the importance of strategic foresight in navigating the complexities of modern technological ecosystems.

Furthermore, the discussions surrounding the funding round highlight the broader trend of “moonshot” investments in the tech industry, where traditional risk-reward calculations are being redefined by the promise of paradigm-shifting discoveries. Investors are increasingly willing to back companies that operate at the frontier of science and technology, even in the absence of immediate financial returns. This willingness is underpinned by the understanding that the breakthroughs achieved by such companies could have far-reaching implications for society at large—ranging from revolutionizing healthcare delivery to reshaping global economic structures. In the case of Safe Superintelligence, the potential to develop AI systems that are not only highly advanced but also inherently safe represents a unique value proposition that resonates deeply with current global priorities.

The evolution of Safe Superintelligence and its ambitious funding targets also serve as a bellwether for the future of artificial intelligence research and commercialization. As the company embarks on what is likely to be one of the most significant capital-raising exercises in the history of AI startups, its progress will be closely monitored by a wide array of stakeholders, including investors, policymakers, academic researchers, and industry competitors. The outcome of these funding negotiations is expected to have a cascading effect on the valuation and strategic direction of similar ventures, potentially setting new benchmarks for what constitutes success in the rapidly evolving AI sector.

In light of these developments, it becomes imperative to consider not only the immediate financial implications of Safe Superintelligence’s high valuation but also the longer-term societal impact of its technological pursuits. The company’s commitment to the development of safe AI systems resonates with broader societal concerns about the ethical and responsible deployment of artificial intelligence. As AI technologies become increasingly integrated into critical aspects of human life, ensuring that these systems are developed with an emphasis on safety and accountability is of paramount importance. By placing safety at the forefront of its innovation agenda, Safe Superintelligence is contributing to a more measured and sustainable approach to technological progress—one that recognizes the potential risks of unchecked innovation while striving to harness its benefits for the greater good.

The transformative potential of Safe Superintelligence, as evidenced by its ambitious funding goals and soaring valuation, is emblematic of the broader trends that are reshaping the global technology landscape. As stakeholders from across the spectrum of industry, academia, and government come together to support the advancement of artificial intelligence, the development of safe and responsible AI systems emerges as a central theme. The company’s trajectory offers a compelling case study in how visionary leadership, combined with strategic investment and a commitment to ethical innovation, can drive profound changes in both market dynamics and technological paradigms.

In conclusion, the current funding discussions surrounding Safe Superintelligence represent a watershed moment in the evolution of artificial intelligence startups. With a valuation of at least $20 billion, the company is poised to accelerate its research efforts, attract further investment, and potentially redefine the parameters of safe AI development. The involvement of high-profile investors and the illustrious track record of its founding team have set the stage for a transformative journey that could yield significant benefits for society as a whole. As the global tech community watches with bated breath, the future of Safe Superintelligence will undoubtedly serve as a powerful indicator of the direction in which AI innovation—and indeed the entire technology sector—is headed. This development not only underscores the rapidly shifting dynamics of startup valuation in the age of artificial intelligence but also highlights the critical importance of aligning technological advancement with principles of safety and ethical responsibility. In the coming months and years, the impact of Safe Superintelligence’s endeavors will likely reverberate across industries and borders, heralding a new chapter in the interplay between innovation, investment, and the transformative potential of human ingenuity.

Subject of Research: Artificial Intelligence, Startup Funding, Valuation Dynamics, Technology Innovation
Article Title : Report: Ilya Sutskever’s Safe Superintelligence in Talks to Fundraise at a Valuation of at Least $20 Billion
News Publication Date :
Article Doi References :
Image Credits : Scienmag
Keywords : Artificial Intelligence, AI Startup, Safe Superintelligence, Ilya Sutskever, Funding, Valuation, Venture Capital, Technology Innovation

The distinguishing attribute of Gemini 2.0 Flash is its capacity to generate and interpret multiple forms of media natively. While its predecessor, Gemini 1.5 Flash, was confined to textual outputs and had relatively limited creative ambition, 2.0 Flash now brings forth a robust suite of capabilities that draw on visual, auditory, and textual modalities simultaneously. This significant enhancement emerges at a critical juncture in the AI landscape. Just as language models have become indispensable tools for summarization, translation, and content generation, there has been an urgent demand for similarly powerful models that can navigate the complexity of visual data, whether in the form of still images, diagrams, or live video feeds. Gemini 2.0 Flash meets this challenge by generating synthetic images from textual prompts, refining existing visuals, and interpreting visual contexts with a level of granularity that could transform industries reliant on image recognition. In an environment where applications range from educational tools that visualize complex concepts to security systems that parse live surveillance feeds, such multimodal proficiency is more than a technological milestone: it is a precursor to richer, more dynamic human-AI collaboration.

This multimodality extends further with the model’s capacity to handle audio. While textual interaction remains at the core of large language models, the ability to produce and comprehend spoken language promises to reshape domains such as accessibility, education, entertainment, and communication assistance. Gemini 2.0 Flash introduces audio narration with customizable voices optimized for different accents and languages. Users might request slower speech for language learners, or employ playful stylistic changes such as instructing the model to “speak like a pirate,” thereby making interactions both more adaptable and more engaging. This flexibility could help language learners immerse themselves in more authentic linguistic environments, while also supporting professionals who require multilingual and cross-cultural communications. Moreover, the model’s capacity to interpret and summarize audio recordings, whether spoken dialogues or lectures, could streamline research workflows, assist with note-taking during meetings, or enhance archival processes by converting long-form audio content into concise, accessible transcripts.

Accompanying these expanded capabilities are improvements in speed, factual reliability, and mathematical reasoning. Early internal benchmarks suggest that Gemini 2.0 Flash outperforms even Google’s own Gemini 1.5 Pro model in certain tasks, operating at roughly twice its speed. Beyond mere acceleration, the model exhibits enhanced competency in logic, arithmetic, and factual accuracy. Such improvements reflect a broader trend in AI development: as models incorporate more modalities, the underlying algorithms and training methodologies are refined to handle complexity more gracefully. The result is a system that is not only faster and more versatile, but also better grounded in reliable information. This is crucial for applications where factual precision and trustworthiness are paramount, such as medical research, financial analysis, academic inquiry, and government policy formulation. Integrating large-scale textual databases, real-time feeds, and external computational tools through APIs, the model can respond to queries with a richer and more contextually informed perspective.

There is, however, a pressing need to address the ethical and security implications of multimodal generation and interpretation. As artificial intelligence grows more adept at producing synthetic images, videos, and sounds—content that can be highly realistic and difficult to distinguish from authentic data—concerns about misinformation, deepfakes, and other forms of manipulation become more urgent. In recent years, the proliferation of AI-generated media has raised public awareness and regulatory scrutiny. Google’s response with Gemini 2.0 Flash is to embed SynthID technology directly into its generative pipeline. SynthID ensures that all generated images and audio contain detectable watermarks, rendering them identifiable as synthetic on compatible software and platforms. This transparency measure seeks to mitigate the risk of malicious use, highlight the model’s synthetic outputs, and foster a responsible relationship with emerging technology. While such interventions will not eliminate risks entirely, they set an important precedent for how major developers integrate safeguards into their platforms, anticipating both the evolving regulatory environment and the broader sociotechnical challenges posed by advanced AI systems.

Gemini 2.0 Flash also stands as a bridge between AI research and the broader ecosystem of application development. Google’s release of the Multimodal Live API invites developers to create real-time, multimodal applications that integrate seamlessly with cameras, microphones, and other streaming inputs. Researchers, engineers, and entrepreneurs may use these capabilities to prototype novel products, enhance user experiences, and push the boundaries of what is technologically achievable. Consider, for instance, a scenario in live journalism where the system interprets a press briefing in real-time, generates bilingual subtitles, highlights key statements, and even offers contextual background sourced from external databases. Another scenario might involve a virtual instructor who not only explains complex scientific concepts through text and voice, but also delivers accompanying illustrative images or animations. By coordinating across these modalities, the model fosters a more immersive learning environment and accelerates knowledge transfer.

From the perspective of software engineering, Gemini 2.0 Flash’s integration with familiar tools such as Android Studio, Chrome DevTools, Firebase, and Gemini Code Assist promises to streamline coding workflows. Its enhanced coding assistance features can offer instantaneous debugging support, suggest alternative libraries, or guide programmers through complex code refactoring. Such capabilities could significantly reduce development time, alleviate the cognitive load on developers, and enable more creative problem solving. As AI-driven code suggestion and debugging become more mainstream, developers might gain the freedom to focus on higher-level strategic decisions, innovative algorithm design, or user-centric product iteration. Ultimately, this could usher in a new era of collaborative intelligence where humans and AI share the creative burden, complement each other’s strengths, and contribute collectively to a more efficient and innovative software development culture.

The implications of Gemini 2.0 Flash’s arrival extend beyond the technical sphere, influencing the daily lives of individuals across sectors. Consumers may soon interact with personal assistants that not only retrieve and summarize information, but also present it in carefully curated multimodal formats. Imagine reading about a historical figure while simultaneously viewing relevant images and listening to an audio narration. Educators can transform lessons into interactive experiences, providing students with spoken commentary, visual references, and text-based summaries tailored to various learning styles. Healthcare professionals, in turn, might leverage the model’s capacity to analyze and summarize patient consultations, generating real-time medical notes that improve diagnostic accuracy and patient care efficiency.

These rapid developments in AI capability, however, must proceed hand-in-hand with a reinvigorated commitment to responsible deployment. As large-scale AI models grow more integrated into human activities, questions of bias, privacy, intellectual property, and access to these tools become ever more pressing. The unveiling of Gemini 2.0 Flash is a reminder that with enhanced potency and complexity come new responsibilities, prompting industry leaders, policymakers, and research communities to collaborate on robust frameworks that balance technological advancement with ethical considerations. The presence of a clearly labeled synthetic output, as enabled by SynthID, may represent just the beginning of a larger global conversation about authenticity, accountability, and trust in digital content.

In the coming months, as the broader release of Gemini 2.0 Flash moves beyond early access partners and into the wider public domain, researchers and developers will have opportunities to test the model’s claims against real-world benchmarks. Such critical evaluation will determine how well its multimodal capabilities translate into practical benefits, whether its enhanced reasoning and factual grounding withstand the complexity of open-ended inquiry, and how the safeguards and transparency measures hold up under the pressures of broad user adoption. The lessons gleaned will resonate across the AI community, setting the tone for the development of subsequent generations of multimodal models.

Just as advanced textual models shifted our understanding of automation, communication, and creative work, these new multimodal systems are poised to redefine how society engages with digital content. Gemini 2.0 Flash’s introduction marks a tangible step in that direction, illuminating paths toward more nuanced, context-sensitive, and interactive AI experiences. Whether in the service of cutting-edge research, practical tools for industry, or everyday assistance for the general public, the capabilities now being realized suggest a future in which artificial intelligence seamlessly mediates between words, images, and sounds, offering integrated solutions to some of our most demanding intellectual and creative challenges. In doing so, it transcends the boundaries of modality and moves closer to an AI that can fluently converse not only in language, but in the entire spectrum of human expression.

Subject of Research

Artificial Intelligence

Article Title

Introducing Gemini 2.0: our new AI model for the agentic era

News Publication Date

Dec 11, 2024

Web References

https://blog.google/technology/google-deepmind/google-gemini-ai-update-december-2024/

References

Google. (2024, December 12). Google Gemini AI update – December 2024. Retrieved December 12, 2024, from https://blog.google/technology/google-deepmind/google-gemini-ai-update-december-2024/

Using peptides and a snippet of the large molecules in plastics, Northwestern University materials scientists have developed materials made of tiny, flexible nano-sized ribbons that can be charged just like a battery to store energy or record digital information. Highly energy efficient, biocompatible and made from sustainable materials, the systems could give rise to new types of ultralight electronic devices while reducing the environmental impact of electronic manufacturing and disposal.

The study was published today (Oct. 9) in the journal Nature.

With further development, the new soft materials could be used in low-power, energy-efficient microscopic memory chips, sensors and energy storage units. Researchers also could integrate them into woven fibers to create smart fabrics or sticker-like medical implants. In today’s wearable devices, electronics are clunkily strapped to the body with a wristband. But, with the new materials, the wristband itself could have electronic activity.

“This is a wholly new concept in materials science and soft materials research,” said Northwestern’s Samuel I. Stupp, who led the study. “We imagine a future where you could wear a shirt with air conditioning built into it or rely on soft bioactive implants that feel like tissues and are activated wirelessly to improve heart or brain function.

“Those uses require electrical and biological signals, but we cannot build those applications with classic electroactive materials. It’s not practical to put hard materials into our organs or in shirts that people can wear. We need to bring electrical signals into the world of soft materials. That is exactly what we have done in this study.”

Stupp is the Board of Trustees Professor of Materials Science and Engineering, Chemistry, Medicine and Biomedical Engineering at Northwestern. He also has served over the past decade as director of the U.S. Department of Energy-supported Center for Bio-Inspired Energy Science, where this research began. Stupp has appointments in the McCormick School of Engineering, Weinberg College of Arts and Sciences and Northwestern University Feinberg School of Medicine. Yang Yang, a research associate in Stupp’s laboratory, is the paper’s first author.

Peptides meet plastics for true innovation

The secret behind the new material is peptide amphiphiles, a versatile platform of molecules previously developed in Stupp’s laboratory. These self-assembling structures form filaments in water and have already demonstrated promise in regenerative medicine. The molecules contain peptides and a lipid segment, which drives the molecular self-assembly when placed in water.

In the new study, the team replaced the lipid tail with a miniature molecular segment of a plastic called polyvinylidene fluoride (PVDF). But they kept the peptide segment, which contains sequences of amino acids. Commonly used in audio and sonar technologies, PVDF is a plastic with unusual electrical properties. It can generate electrical signals when pressed or squeezed — a property known as piezoelectricity. It also is a ferroelectric material, which means it has a polar structure that can switch orientation by 180 degrees using an external voltage. The dominant ferroelectrics in technology are hard materials and often include rare or toxic metals, such as lead and niobium.

“PVDF was discovered in the late 1960s and is the first known plastic with ferroelectric properties,” Stupp said. “It has all the robustness of plastic while being useful for electrical devices. That makes it a very high-value material for advanced technologies. However, in pure form, its ferroelectric character is not stable, and, if heated above the so-called Curie temperature, it loses its polarity irreversibly.”

All plastics, including PVDF, contain polymers, which are giant molecules typically composed of thousands of chemical structural units. In the new study, the Stupp laboratory precisely synthesized miniature polymers with only three to seven vinylidene fluoride units. Interestingly, the miniature segments with four, five or six units are programmed by nature’s beta-sheet structures, which are present in proteins, to organize into a stable ferroelectric phase.

“It was not a trivial task,” Stupp said. “The combination of two unlikely partners — peptides and plastics — led to a breakthrough in many respects.”

Not only were the new materials equally ferroelectric and piezoelectric as PVDF, but the electroactive forms were stable, with the ability to switch polarity using extremely low external voltages. This opens the door for low-power electronics and sustainable nanoscale devices. The scientists also envision developing new biomedical technologies by attaching bioactive signals to the peptide segments, a strategy already used in Stupp’s regenerative medicine research. This offers the unique combination of electrically active materials that are also bioactive.

Just add water

To create the sustainable structures, Stupp’s team simply added water to trigger the self-assembly process. After dunking the materials, Stupp was amazed to find that they achieved the highly sought-after ferroelectric properties of PVDF.

In the presence of an external electric field, ferroelectric materials flip their polar orientation — similar to how a magnet can be flipped from north to south and back again. This property is a key ingredient for devices that store information, an important feature for artificial intelligence technologies. Surprisingly, the investigators found that “mutations” in the peptide sequence could tune properties related to ferroelectricity or even transform the structures into materials that are ideal for actuation or energy storage known as “relaxor phases.”

“Peptide sequence mutations in biology are the source of pathologies or biological advantages,” Stupp said. “In the new materials, we mutate peptides to tune their properties for the physical world.

“Using nanoscale electrodes, we could potentially expose an astronomical number of self-assembling structures to electric fields. We could flip their polarity with a low voltage , so one serves as a ‘one,’ and the opposite orientation serves as a ‘zero.’ This forms binary code for information storage. Adding to their versatility, and in great contrast to common ferroelectrics, the new materials are ‘multiaxial’ — meaning they can generate polarity in multiple directions around a circle rather than one or two specific directions.”

Record-breaking low power

To flip their polarity, even soft ferroelectric materials like PVDF or other polymers typically require a substantial external electric field. The new structures, however, require incredibly low voltage.

“The energy required to flip their poles is the lowest ever reported for multiaxial soft ferroelectrics,” Stupp said. “You can imagine how much energy this will save in increasingly energy-hungry times.”

The new materials also have innate environmental benefits. Unlike typical plastics, which linger in the environment for centuries, the Stupp laboratory’s materials could be biodegraded or reused without the use of harmful, toxic solvents or high-energy processes.

“We are now considering the use of the new structures in non-conventional applications for ferroelectrics, which include biomedical devices and implants as well as catalytic processes important in renewable energy,” Stupp said. “Given the use of peptides in the new materials, they lend themselves to functionalization with biological signals. We are very excited about these new directions.”

The study, “Peptide programming of a supramolecular vinylidene fluoride ferroelectric phase,” was supported by the U.S. Department of Energy (awards DE-SC0020884 and DE-SC0000989).

Journal Reference:

Yang Yang, Hiroaki Sai, Simon A. Egner, Ruomeng Qiu, Liam C. Palmer, Samuel I. Stupp. Peptide programming of supramolecular vinylidene fluoride ferroelectric phases. Nature, 2024; DOI: 10.1038/s41586-024-08041-4

Journal

Nature

DOI

10.1038/s41586-024-08041-4 

Article Title

Peptide programming of supramolecular vinylidene fluoride ferroelectric phases

Mira Murati, OpenAI’s Chief Technology Officer, led the presentation and highlighted the model’s key advancements. She emphasized that GPT-4o provides “GPT-4-level intelligence” but significantly extends its capabilities across multiple modalities. Murati stated, “GPT-4o reasons across voice, text, and vision. This is incredibly important because we’re looking at the future of interaction between ourselves and machines.”

One of the most immediate applications of GPT-4o is its integration into OpenAI’s widely-used chatbot, ChatGPT. Previously, ChatGPT offered a voice mode that transcribed responses using a text-to-speech model. However, GPT-4o revolutionizes this feature, allowing users to interact with ChatGPT in a more dynamic and natural manner. Users can now interrupt the chatbot mid-response, engage in real-time conversations, and experience responses that reflect different emotive styles, including singing. This enhancement makes ChatGPT more effective as a personal assistant, providing a more fluid and lifelike user experience.

Murati demonstrated how GPT-4o’s enhanced vision capabilities enable it to analyze photos and screenshots, offering detailed explanations and answers. For example, users can inquire about the content of software code displayed on a screen or identify the brand of a shirt in a photograph. These capabilities are particularly useful for professionals in tech and retail industries, where quick and accurate visual analysis is crucial.

The multilingual capabilities of GPT-4o are another area of significant improvement. The model supports around 50 languages with enhanced performance, making it more versatile for global applications. This advancement is particularly beneficial for businesses operating in multilingual environments, as it allows for more effective communication and better customer service. Murati noted that GPT-4o’s ability to handle multiple languages at a higher performance level makes it an invaluable tool for global operations.

In addition to its enhanced capabilities, GPT-4o offers significant improvements in performance and cost efficiency. According to Murati, GPT-4o is twice as fast and half the price of GPT-4 Turbo, OpenAI’s previous leading model. This makes the new model more accessible to developers and businesses, enabling them to leverage cutting-edge AI technology without prohibitive costs.

Murati also discussed the future potential of GPT-4o. She envisions scenarios where the model could “watch” a live sports game and explain the rules to users in real-time. This capability would represent a significant advancement in AI’s ability to understand and interact with dynamic, real-world environments. Such advancements hint at a future where AI can provide real-time insights and support in a variety of complex situations.

OpenAI has introduced several new features to complement the launch of GPT-4o, aimed at improving user experience. The refreshed ChatGPT user interface includes a more conversational home screen and an updated message layout. Additionally, OpenAI has released a desktop app for macOS, enabling users to ask questions via a keyboard shortcut or take and discuss screenshots directly within the app. These enhancements are designed to make interactions with ChatGPT more intuitive and seamless.

Starting today, GPT-4o is available in the free tier of ChatGPT. Subscribers to OpenAI’s premium ChatGPT Plus and Team plans benefit from “5x higher” message limits, enhancing their ability to leverage the model’s capabilities. The improved voice experience, currently in alpha, will be available to Plus users in the coming month, with enterprise-focused options also on the horizon.

Overall, OpenAI’s unveiling of GPT-4o marks a significant advancement in the field of artificial intelligence. Its multimodal capabilities, enhanced multilingual support, and cost efficiency set a new standard for AI interaction. The model’s integration into ChatGPT and the introduction of new features ensure a more natural and dynamic user experience. As AI technology continues to evolve, GPT-4o’s innovative capabilities promise to transform how humans interact with machines, paving the way for a more intuitive and integrated future.

————————————————————————- ###

About Korea Institute of Materials Science(KIMS) KIMS is a non-profit government-funded research institute under the Ministry of Science and ICT of the Republic of Korea. As the only institute specializing in comprehensive materials technologies in Korea, KIMS has contributed to Korean industry by carrying out a wide range of activities related to materials science including R&D, inspection, testing&evaluation, and technology support.

Journal

Small Methods

DOI

10.1002/smtd.202300969

Article Title

Nanocrystalline Composite Layer Realized by Simple Sintering Without Surface Treatment, Reducing Hydrophilicity and Increasing Thermal Conductivity

Article Publication Date

14-Dec-2023

The new technique could help scientists improve the inner workings of a range of “nanoelectronics,” including the miniature semiconductors in computer chips. The discovery was highlighted Dec. 1 in a special issue of “Optics & Photonics News” called “Optics in 2023.”

The research is the latest advance in the field of ptychography, a difficult to pronounce (the “p” is silent) but powerful technique for viewing very small things. Unlike traditional microscopes, ptychography tools don’t directly view small objects. Instead, they shine lasers at a target, then measure how the light scatters away—a bit like the microscopic equivalent of making shadow puppets on a wall.

So far, the approach has worked remarkably well, with one major exception, said study senior author and Distinguished Professor of physics Margaret Murnane.

“Until recently, it has completely failed for highly periodic samples, or objects with a regularly repeating pattern,” said Murnane, fellow at JILA, a joint research institute of CU Boulder and the National Institute of Standards and Technology (NIST). “It’s a problem because that includes a lot of nanoelectronics.”

She noted that many important technologies like some semiconductors are made up of atoms like silicon or carbon joined together in regular patterns like a grid or mesh. To date, those structures have proved tricky for scientists to view up close using ptychography.

In the new study, however, Murnane and her colleagues came up with a solution. Instead of using traditional lasers in their microscopes, they produced beams of extreme ultraviolet light in the shape of doughnuts.

The team’s novel approach can collect accurate images of tiny and delicate structures that are roughly 10 to 100 nanometers in size, or many times smaller than a millionth of an inch. In the future, the researchers expect to zoom in to view even smaller structures. The doughnut, or optical angular momentum, beams also won’t harm tiny electronics in the process—as some existing imaging tools, like electron microscopes, sometimes can.

“In the future, this method could be used to inspect the polymers used to make and print semiconductors for defects, without damaging those structures in the process,” Murnane said.

Bin Wang and Nathan Brooks, who earned their doctoral degrees from JILA in 2023, were first authors of the new study.

Pushing the limits of microscopes
The research, Murnane said, pushes the fundamental limits of microscopes: Because of the physics of light, imaging tools using lenses can only see the world down to a resolution of about 200 nanometers—which isn’t accurate enough to capture many of the viruses, for example, that infect humans. Scientists can freeze and kill viruses to view them with powerful cryo-electron microscopes but can’t yet capture these pathogens in action and in real time.

Ptychography, which was pioneered in the mid-2000s, could help researchers push past that limit.

To understand how, go back to those shadow puppets. Imagine that scientists want to collect a ptychographic image of a very small structure, perhaps letters spelling out “CU.” To do that, they first zap a laser beam at the letters, scanning them multiple times. When the light hits the “C” and the “U” (in this case, the puppets), the beam will break apart and scatter, producing a complex pattern (the shadows). Employing sensitive detectors, scientists record those patterns, then analyze them with a series of mathematical equations. With enough time, Murnane explained, they recreate the shape of their puppets entirely from the shadows they cast.

“Instead of using a lens to retrieve the image, we use algorithms,” Murnane said.

She and her colleagues have previously used such an approach to view submicroscopic shapes like letters or stars.

But the approach won’t work with repeating structures like those silicon or carbon grids. If you shine a regular laser beam on a semiconductor with such regularity, for example, it will often produce a scatter pattern that is incredibly uniform—ptychographic algorithms struggle to make sense of patterns that don’t have much variation in them.

The problem has left physicists scratching their heads for close to a decade.

Doughnut microscopy
In the new study, however, Murnane and her colleagues decided to try something different. They didn’t make their shadow puppets using regular lasers. Instead, they generated beams of extreme ultraviolet light, then employed a device called a spiral phase plate to twist those beams into the shape of a corkscrew, or vortex. (When such a vortex of light shines on a flat surface, it makes a shape like a doughnut).

The doughnut beams didn’t have pink glaze or sprinkles, but they did the trick. The team discovered that when these types of beams bounced off repeating structures, they created much more complex shadow puppets than regular lasers.

To test out the new approach, the researchers created a mesh of carbon atoms with a tiny snap in one of the links. The group was able to spot that defect with precision not seen in other ptychographic tools.

“If you tried to image the same thing in a scanning electron microscope, you would damage it even further,” Murnane said.

Moving forward, her team wants to make their doughnut strategy even more accurate, allowing them to view smaller and even more fragile objects—including, one day, the workings of living, biological cells.

Other co-authors of the new study include Henry Kapteyn, professor of physics and fellow of JILA, and current and former JILA graduate students Peter Johnsen, Nicholas Jenkins, Yuka Esashi, Iona Binnie and Michael Tanksalvala.

Journal
Optica

DOI
10.1364/OPTICA.498619

Article Title
High-fidelity ptychographic imaging of highly periodic structures enabled by vortex high harmonic beams

Article Publication Date
20-Sep-2023

Disclaimer: AAAS and

The new East Lansing facility will be what amounts to the third act for the K500, which burst onto the nuclear science scene 40 years ago, making history as the world’s first superconducting cyclotron.

“This new FRIB-adjacent facility at MSU will provide the United States several thousand additional hours of capacity for chip testing annually,” said MSU Interim President Teresa K. Woodruff, Ph.D. “We are ready to leverage a six-decade-long investment by the National Science Foundation in basic nuclear science at MSU for a new purpose that is so central to this critical industry, to U.S. competitiveness, and to national security.”

Among the most immediate goals is the testing of electronic components for use in space, where levels of ionizing radiation are much higher than at the Earth’s surface and where devices must operate for years or even decades with little if any maintenance. The MSU proposal for funding was in direct response to the 2018 National Academies report, “Testing at the Speed of Light,” which outlined a critical national shortfall of testing capacity of space-bound electronic components.

New chapter, same story

The K500’s newest chapter – one relevant to daily headlines that cut across the domains of geopolitics, business and technology – is set to continue a long MSU story of fueling disruptive innovation to create novel physics hardware, which is then leveraged to create sustained and broad-based benefits to support the nation. Perhaps the most prominent example of this pattern: a near copy of the K500 operates today at Texas A&M University where it’s used for nuclear physics research.

“MSU has been purposeful in leveraging its accelerator assets for new applications over the course of its nearly 60-year history in accelerator-based nuclear science leadership,” explained Thomas Glasmacher, FRIB Laboratory director. “This award enables us to continue that tradition at FRIB while delivering on our mission of addressing societal problems by providing this additional resource to advance current U.S. interests.”

The K500’s first act ushered in the superconducting cyclotron era for research with heavy ions. It was built on a shoestring budget, as is typical for the one-of-a-kind nature of devices in accelerator physics, and was often quite unreliable in its early days. Act two followed a hiatus and refurbishment in the late 1990s for coupling with the more powerful K1200 cyclotron. Initially approved by the NSF in 1996, the Coupled Cyclotron Facility (CCF) began operations in 2001 and was used more or less continually until November 2020. It enabled research with fast rare isotope beams at the National Superconducting Cyclotron Laboratory (NSCL), supported by the NSF. Among other things, the lab was known for its efficiency and uptime, eventually surpassing 90 percent, which is noteworthy given the complexity of the equipment.

This track record loomed large in MSU’s successful bid for FRIB, which the FRIB Project team built ahead of schedule and on budget. FRIB experiments are underway using what will be the world’s most powerful heavy-ion linear accelerator (linac).

The new linac might have finally spelled the end of the lower energy K500. However, in a pattern that has recurred in the history of innovation, the older technology instead has found new and, given the more than $500 billion semiconductor market and strategic importance of the chip industry, perhaps even wider relevance.

“The laboratory has always had an emphasis on building instruments that advanced the options available for solving basic and applied research problems in nuclear science,” said Andreas Stolz, MSU professor and FRIB rare isotope operations department manager. “We are excited to apply our operational expertise and the K500 cyclotron to a new purpose, especially one so relevant to the national interest.” Stolz is the principal investigator on the MDA contract.

Creating an ‘unparalleled ecosystem’

The new facility will complement a host of related work and initiatives at MSU and furthers university leadership in nuclear science, microelectronics and semiconductors. FRIB’s Single Event Effects (FSEE) facility is already operational, offering a menu of beams and ion cocktails for use in research. Another example: MSU’s new Space Electronics Center, a collaboration with Texas Instruments, was announced this fall and leverages FRIB to provide a range of services to industry, including research projects, workforce development, technical workshops and forums for small corporate delegations to have a presence on MSU’s campus. MSU’s nuclear physics graduate program has been ranked No. 1 since 2010 by U.S. News and World Report.

“MSU, FRIB and the College of Engineering, through the Space Electronics Center, are creating an unparalleled ecosystem that will include strong industry and government participation to advance the state-of-the-art in radiation-hardened components and space electronics, and above all, to develop the necessary talent that will support this technology discipline for years to come and solidify the U.S. position as a leader in this field,” said John Papapolymerou, MSU Research Foundation Professor and chair of the MSU Electrical and Computer Engineering Department.

Use of the new MSU facility will extend far beyond defense and aerospace applications since today more than ever, the semiconductor industry is marked by the creation of ever smaller, denser and more complex custom circuitry. Following the broad outlines of Moore’s Law, the industry has delivered a steady march of faster, cheaper and more power-efficient computing technologies for decades. Advanced semiconductor devices, with nanometer-scale features and often purpose-built with stacked interconnected chips to further increase capability, are increasingly susceptible to ionizing radiation.

Usually such effects – bit-flips of memory elements in a chip – don’t permanently damage the device. However, there are examples of real-world problems, from the trivial (impacting the outcome of a 2013 Super Mario game contest) to the more serious (causing injuries on a 2008 Qantas flight, which plunged downward when the onboard computer malfunctioned.) Risks only increase as more of daily life becomes dependent on applications ultimately mediated by computer hardware and software.

“Space electronics applications can act as a catalyst to attract a brand-new generation of engineers and scientists needed to fill the more than 50,000 positions in the general area of semiconductors over the next five years or so, said Papapolymerou. “MSU will play a central and pivotal role in this talent pipeline development.”

Experts, experience will guide the next transition

FRIB will draw on a deep well of institutional and operational expertise to transition the K500 cyclotron into its third act.

“Downtime to tune the equipment or fix problems is expensive, not only in dollars but also in lost opportunities for discovery and education, so we’ve long been incentivized to be efficient and meet the needs of our experimenters,” says Sam Austin, University Distinguished Professor Emeritus in nuclear physics and former NSCL Director. “We’re proud of our culture and approach, which is to do what it takes to make our users successful.”

NSF investment in accelerator-related research at MSU dates back to 1961 and resulted in many important advances in basic and applied rare isotope research, many of which are outlined in Austin’s 2016 book “Up from Nothing.” These advances include dozens of examples of experimental apparatus and techniques, from spectrographs to superconducting solenoids to stopping fast beams.

“This is really about the value of sustained vision and concomitant actions over decades,” said Glasmacher. “Part of building resiliency in U.S. science and technology, whether in nuclear science or semiconductors, is not to forget work that’s come before, but rather to leverage assets for future discoveries.”

###

Michigan State University has been advancing the common good with uncommon will for more than 165 years. One of the world’s leading research universities, MSU pushes the boundaries of discovery to make a better, safer, healthier world for all while providing life-changing opportunities to a diverse and inclusive academic community through more than 400 programs of study in 17 degree-granting colleges.

However, it is not clear how the human brain responds to robots in empathic situations.

Now, researchers at the Department of Information Science and Engineering, Toyohashi University of Technology in collaboration with researchers at the Department of Psychology, Kyoto University have found the first neurophysiological evidence of humans’ ability to empathize with robots in perceived pain and highlighted the difference in human empathy toward other humans and robots.

They performed electroencephalography (EEG) in 15 healthy adults who were observing pictures of either a human or robotic hand in painful or non-painful situations, such as a finger being cut by a knife. Event-related brain potentials for empathy toward humanoid robots in perceived pain were similar to those for empathy toward humans in pain. However, the beginning of the top-down process of empathy was weaker in empathy toward robots than toward humans.

“The ascending phase of P3 (350-500 ms after the stimulus presentation) showed a positive shift in the observer for a human in pain in comparison with the no-pain condition, but not for a robot in perceived pain. Then, the difference between empathy toward humans and robots disappeared in the descending phase of P3 (500-650 ms)”, explains Associate Professor Michiteru Kitazaki, “The positive shift of P3 is considered as reflecting the top-down process of empathy. Its beginning phase seems related to the process of perspective taking, as was shown in a previous study.”

These results suggest that we empathize with humanoid robots in a similar fashion as we do with other humans. However, the beginning of the top-down process of empathy is weaker for empathy toward robots than toward humans. It may be caused by humans’ inability in taking a robot’s perspective.

It is reasonable that we cannot take the perspective of robots because their body and mind (if it exists) are very different from ours. The researchers are trying to manipulate humans’ perspective taking of robots in a further study. This study will contribute to the development of human-friendly robots whom we feel sympathy for and comfortable with.

###

This study was partly supported by a Grant-in-Aid for Scientific Research (A) #25245067, #25240020, and #26240043 by JSPS, MEXT, Japan.

Reference:
Suzuki, Y., Galli, L., Ikeda, A., Itakura, S. and Kitazaki, M. (2015).
Measuring empathy for human and robot hand pain using electroencephalography. Scientific Reports, 5:15924; doi:
10.1038/srep15924

Further information

Toyohashi University of Technology
1-1 Hibarigaoka, Tempaku
Toyohashi, Aichi Prefecture, 441-8580, JAPAN
Inquiries: Committee for Public Relations
E-mail: press@office.tut.ac.jp

Toyohashi University of Technology, which was founded in 1976 as a National University of Japan, is a leading research institute in the fields of mechanical engineering, advanced electronics, information sciences, life sciences, and architecture.

Website: http://www.tut.ac.jp/english/