Ayar Labs (United States)

In recent high-speed serial interfaces, multi-level modulation has been widely adopted to improve bandwidth efficiency [1], [2], [3], [4]. As a result, flexibility in modulation schemes and robustness against various channel conditions have become critical requirements in transmitter (TX) design. The differences between analog based TX and digital signal processing (DSP) based TX are shown in Fig. 1. While analog-based TXs offer the advantage of low power consumption, the high-speed operation of the feedforward equalizer (FFE) imposes stringent timing constraints. Furthermore, they inherently lack flexibility in modulation schemes, and the hardware complexity increases with the number of FFE taps, as the data path size must scale accordingly [5]. As a result, analog implementations face limitations in effectively compensating for inter-symbol interference (ISI). In contrast, DSP-based TXs perform equalization through low-speed parallel processing, which significantly alleviates the timing constraints. The digital architecture also enables programmable allocation of pre- and post-cursor taps under a fixed tap budget. This provides improved configurability and adaptability over analog designs with fixed tap locations. This paper presents a DSP-based TX supporting NRZ, PAM-4, and PAM-8 modulation. A 14-tap FFE implemented within the DSP effectively compensates for ISI over channels with 17.3 dB insertion loss at the Nyquist frequency.

The present study is aimed with an objective to produce bio ethanol from agrowaste. Paddy straw bio mass is collected from agricultural land and utilized as feed stock for ethanol production after subjecting them to acid, alkali and enzymatic pre treatments. Two bacterial strains (R2 and R3) and one yeast strain (S6) were isolated from soil samples collected from paddy field dumped with straw and from sugarcane bagasse dumped soil. In addition to this, cellulose degrading bacteria strain (C1) is isolated to carry out the enzymatic pre treatment. Based on the fermentation efficiency tested, S6, R2 and R3 strains were inoculated in eight different pretreated biomass filtrate medium for fermentation process. Ethanol concentration were quantified at a period of five days interval up to twenty days. Ethanol concentration increased from 5th day to 20th day and 5th day to 15th day in yeast and bacteria inoculated medium. After recovery through distillation, yeast strain S6 inoculated medium is reported with more concentration of ethanol in alkali pre treated bio mass filtrate medium. There is no significant difference between alkali pre treated biomass and combined alkali & enzyme pre treated bio mass inoculated with yeast strain at 0.001 level of significance. The overall product extracted is in the range of 5-12%. Ethanol extracted from yeast S6 is reported to have disinfectant effect against bacteria. FTIR spectrum analysis reported the presence of similar peaks to that of standard ethanol

We demonstrate a UCIe Optical I/O Retimer for scale-up AI fabrics. It achieves 1.024Tbps of bidirectional bandwidth per optical port from one package to another, delivering an aggregate bandwidth of 8.192Tbps.

<p>The ‘brain-mind-intelligence’ structure may be considered analogous to a ‘computer-operating system (OS)-application’ construct. Software development would be far more difficult without the benefit of abstractions like file and memory handles, and graphical user interfaces, implemented in operating systems. The easy access to application-level semantics, provided by the infrastructure of the OS, simplifies application development. Abstractions can play a similar role in producing intelligent systems. The power of abstractions may be determined by their ability to unify the treatment of several types of higher concepts. Unifying various concepts in the domain of intelligence, such as problems, solutions, objects, and emotions, through abstractions, will be of immense value. This paper shows how ‘higher-level perceptions’ could be used to serve this objective and construct an OS-like infrastructure. With the infrastructure in place, ordinary software objects developed and deployed using standard methods, become accessible using the semantics provided by the infrastructure. Now, after brief training exercises, the objects would be available for intelligent use. The focus, therefore, is on the design of the infrastructure that could play a mind-like role in humans, using some ideas from philosophers like Kant, Wittgenstein, Heidegger, and Popper.</p> <p>The design uses a new, non-symbolic, non-connectionist, transmutable method of representation that tackles the so-called ‘frame’ and ‘grounding’ problems of artificial intelligence. The infrastructure enables the conversion of sensory inputs to transmutable representations (amenable to semantic modifications), to flexibly act on software objects developed externally. Furthermore, the infrastructure serves to ground and functionally manage the transmutable, connectionist, and symbolic systems. Thus, the new model plays a critical role in building intelligent systems that overcome major problems in learning and action selection, including brittleness associated with the limited semantics of purely symbolic and connectionist designs. </p> <p>The new model is then evaluated in terms of features, against criteria set forth independently by Newell, Sun, Vernon, and others. In addition, a new measure of intelligence introduced in this paper is used to quantitatively compare the proposed model with some others developed over the years.</p>

<p>The ‘brain-mind-intelligence’ structure may be considered analogous to a ‘computer-operating system (OS)-application’ construct. Software development would be far more difficult without the benefit of abstractions like file and memory handles, and graphical user interfaces, implemented in operating systems. The easy access to application-level semantics, provided by the infrastructure of the OS, simplifies application development. Abstractions can play a similar role in producing intelligent systems. The power of abstractions may be determined by their ability to unify the treatment of several types of higher concepts. Unifying various concepts in the domain of intelligence, such as problems, solutions, objects, and emotions, through abstractions, will be of immense value. This paper shows how ‘higher-level perceptions’ could be used to serve this objective and construct an OS-like infrastructure. With the infrastructure in place, ordinary software objects developed and deployed using standard methods, become accessible using the semantics provided by the infrastructure. Now, after brief training exercises, the objects would be available for intelligent use. The focus, therefore, is on the design of the infrastructure that could play a mind-like role in humans, using some ideas from philosophers like Kant, Wittgenstein, Heidegger, and Popper.</p> <p>The design uses a new, non-symbolic, non-connectionist, transmutable method of representation that tackles the so-called ‘frame’ and ‘grounding’ problems of artificial intelligence. The infrastructure enables the conversion of sensory inputs to transmutable representations (amenable to semantic modifications), to flexibly act on software objects developed externally. Furthermore, the infrastructure serves to ground and functionally manage the transmutable, connectionist, and symbolic systems. Thus, the new model plays a critical role in building intelligent systems that overcome major problems in learning and action selection, including brittleness associated with the limited semantics of purely symbolic and connectionist designs. </p> <p>The new model is then evaluated in terms of features, against criteria set forth independently by Newell, Sun, Vernon, and others. In addition, a new measure of intelligence introduced in this paper is used to quantitatively compare the proposed model with some others developed over the years.</p>

<p>The ‘brain-mind-intelligence’ structure may be considered analogous to a ‘computer-operating system (OS)-application’ construct. Software development would be far more difficult without the benefit of abstractions like file and memory handles, and graphical user interfaces, implemented in operating systems. The easy access to application-level semantics, provided by the infrastructure of the OS, simplifies application development. Abstractions can play a similar role in producing intelligent systems. The power of abstractions may be determined by their ability to unify the treatment of several types of higher concepts. Unifying various concepts in the domain of intelligence, such as problems, solutions, objects, and emotions, through abstractions will be of immense value. This paper shows how ‘higher-level perceptions’ could be used to serve this objective and construct an OS-like infrastructure. With the infrastructure in place, ordinary software objects developed and deployed using standard methods, become accessible using the semantics provided by the infrastructure. Now, after brief training exercises, the objects would be available for intelligent use. The focus, therefore, is on the design of the infrastructure that could play a mind-like role in humans.</p> <p>The design uses a new, non-symbolic, non-connectionist, transmutable method of representation that tackles the so-called ‘frame’ and ‘grounding’ problems of artificial intelligence. The infrastructure enables the conversion of sensory inputs to transmutable representations amenable to semantic modifications, to flexibly determine actions to perform on software objects developed externally. Furthermore, the infrastructure serves to ground and functionally manage the transmutable, connectionist, and symbolic systems. Thus, the new model plays a critical role in building intelligent systems that overcome major problems in learning and action selection, including brittleness associated with the limited semantics of purely symbolic and connectionist designs. </p> <p>The new model is then evaluated in terms of features, against criteria set forth independently by Newell, Sun, Vernon, and others. In addition, a new measure of intelligence introduced in this paper is used to quantitatively compare the proposed model with some others developed over the years. </p>

<p>The ‘brain-mind-intelligence’ structure may be considered analogous to a ‘computer-operating system (OS)-application’ construct. Software development would be far more difficult without the benefit of abstractions like file and memory handles, and graphical user interfaces, implemented in operating systems. The easy access to application-level semantics, provided by the infrastructure of the OS, simplifies application development. Abstractions can play a similar role in producing intelligent systems. The power of abstractions may be determined by their ability to unify the treatment of several types of higher concepts. Unifying various concepts in the domain of intelligence, such as problems, solutions, objects, and emotions, through abstractions will be of immense value. This paper shows how ‘higher-level perceptions’ could be used to serve this objective and construct an OS-like infrastructure. With the infrastructure in place, ordinary software objects developed and deployed using standard methods, become accessible using the semantics provided by the infrastructure. Now, after brief training exercises, the objects would be available for intelligent use. The focus, therefore, is on the design of the infrastructure that could play a mind-like role in humans. </p> <p>The resulting model is then evaluated in terms of features against criteria set forth independently, by Newell, Sun, Vernon, and others. In addition, a new measure of intelligence introduced in this paper is used to compare the proposed modeling method with some of the major methods developed over the years.</p> <p><br></p>

This paper aims to give an outlook of future advanced antenna systems for 5G and 6G wireless networks. The trend to increase the peak data rate and to reduce latency and power consumption will continue in the future. This will be made possible by the exploitation of millimeter wave frequency bands and by the introduction of massive multiple-input multiple-output antenna technology which requires a transformation of the antenna hardware architectures and technologies. Advanced antenna systems based on arrays of several hundreds of antenna elements are under development and to keep the fronthaul throughput manageable, some digital signal processing functions have been moved inside the antenna, creating the need to distribute very big volumes of data at high bit rate across the antenna. The characteristics and hardware architecture of future advanced antenna systems are discussed and the relevant interconnect requirements are presented. A new type of monolithically integrated optical transceiver is presented, integrating electronic and photonic circuits on the same chip with high bandwidth density, high energy efficiency and low latency. The transceiver technology is discussed and results of experimental demonstrations are given.

We present a bang-bang phase-locked loop (PLL) generator that encapsulates design methodologies for its circuit blocks and the complete PLL system. The generator is fully automated and parameterized, producing the layout and schematic based on process characterization and top-level specifications. Three 14GHz PLLs are instantiated in TSMC 16nm, GF 14nm and Intel 22nm technologies, demonstrating the process portability. The rapid generation time of less than four days enables fast PLL design and technology porting. The PLL design fabricated in TSMC 16nm shows RMS jitter of 565.4fs and power of 6.64mW from a 0.9V supply.

We present a new switching architecture that is wavelength selective and can multicast. We compare the switch loss, number of elements and crosstalk with multi-wavelength selective crossbar switch. We report reduction in number of elements of 50%, reduced loss and a similar crosstalk as compared with multi-wavelength selective crossbar switch.