If you have been watching the world of artificial intelligence (AI), then you see science fiction come to life before your eyes. Not only are we watching it achieve incredible feats, but we are also seeing them created at an amazing rate. It's just a matter of time before AI becomes a normal functioning member of our society. Those who are resistant to change and new methods are in for a rough time. This is because more and more of our society's occupations will rely on AI in some form or fashion.

Advances in peripheral nervous system (PNS) interfacing present a promising alternative to traditional neuromodulation ([ 1 ][1]), particularly for individuals with upper-limb amputations ([ 2 ][2]–[ 7 ][3]). Implanted electrodes have been shown to diminish phantom limb pain (PLP) in such subjects and enable close-to-natural touch sensations. Individuals with peripheral neural stimulators are even able to control the amount of force exerted by a prosthesis and to discern among objects with different compliances and shapes with prosthesis ([ 2 ][2]–[ 5 ][4]). Successive studies have shown the long-term utility of these technologies ([ 6 ][5], [ 7 ][3]). Having successfully achieved functional stimulation and chronic biocompatibility through neural interfaces, the focus of neuromodulation research is shifting toward achieving optimal design and policy of use ([ 8 ][6]). There is great variety in electrode geometries, stimulating contact numbers, and placement within the nervous system (see the figure) as well as in possible stimulation protocols. Optimization will not be achieved with brute force but requires the development of computational models ([ 9 ][7], [ 10 ][8]) capable of exploiting the knowledge that has been accumulated on this topic. Until recently, most research has focused on hand amputees, neglecting the clinical reality that four out of five amputees have lower-limb loss. Subjects with lower-limb amputation frequently do not engage fully in everyday activities because they are afraid of falls and do not perceive the prosthesis as part of their body (low “embodiment”). Such individuals often report poor satisfaction with their prostheses, citing the prosthesis as an excessive weight, despite prosthetic limbs typically being less than half the weight of a natural limb ([ 11 ][9]). They also tend to have reduced mobility ([ 12 ][10]), which can induce a sedentary lifestyle that promotes disease development and hinders reinsertion into society. PLP is also common and is poorly managed with current medications ([ 13 ][11]). Additionally, those with lower-limb amputations face substantially higher metabolic costs while walking, resulting in an increased risk of heart attack compared with the general population ([ 14 ][12]). We have pioneered a human-machine system that translates prosthetic sensors' readouts into “language” understandable by the nervous system, using a detailed computational model ([ 9 ][7], [ 10 ][8]) that indicates an optimal number of implants for the targeted nerve. Compared with traditional frequency variation, the model favors current amplitude modulation, for increasing efficiency of mapping and closed-loop stimulation ([ 15 ][13]). Placement of the cable connecting implants to the stimulator is a longstanding problem and a frequent cause of failure in implantable technologies during clinical testing ([ 7 ][3], [ 8 ][6]). We addressed this issue during surgical preparation by implementing a release loop and stabilization within the fascia tissue graft with cables embedded in the middle ([ 14 ][12]). We developed a “sensing leg,” for lower-limb amputees, by connecting sensors from the prosthetic knee and under the foot to the residual PNS (see the figure). An effective connection was achieved by equipping a microprocessor-controlled prosthesis with a purposely developed sensorized insole. An external controller that communicates wirelessly with the “sensorized prosthesis” proportionally transduces the readout of the insole and knee sensors into stimulation parameters. The stimulator then injects the current into the intraneural electrodes, eliciting sensations from the missing lower limb. The whole process ran at a delay unperceivable to the user, enabling real-time neuromodulation dependent on leg status. This intervention enabled recovery of rich leg and foot perceptions (such as touch, proprioception, and both simultaneously). Users were able to recognize when the prosthetic leg—physically disconnected from their body and communicating wirelessly with the implants—was touched over different foot positions, flexed, or both. Users were also able to avoid a substantially higher number of stumbles when walking over obstacles, while wearing glasses that blind their lower field of vision, than when not exploiting the restored feedback. Climbing stairs is often a challenge for above-knee amputees, resulting in very slow motion and considerable fatigue. When neuromodulation restored limb perception, their mobility substantially increased ([ 15 ][13]). After these laboratory tests, volunteers stepped outside into a more natural environment. Because of the fully portable neuromodulating system, their confidence was increased, and subjects were able to walk with increased speed over what would normally be challenging sandy terrain. At the same time, volunteers' metabolic consumption was diminished when sensory neurofeedback was switched on. The decreased energy expenditure when using neuromodulation could potentially limit cardiovascular system fatigue—a tremendously important health benefit for lower-limb amputees ([ 14 ][12]). When the implantable system was used in “neuro-pacemaker modality”—stimulating the nerve without connection to the prosthesis—a reduction in PLP was observed. Through precise somatotopic stimulation, we have evoked pleasant, close-to-natural sensations within regions of referred pain. By contrast, commercial stimulation devices mainly deliver prefixed and often ineffective patterns of stimuli, which do not elicit physiologically plausible sensations and fail to deliver effective relief ([ 16 ][14]), and spinal cord stimulators involve the induction of paresthesia (an uncomfortable tingling), which does not always completely relieve the pain ([ 17 ][15]). Meanwhile, neurostimulators that directly target the peripheral nerve deliver either nonselective stimulation or induce an analgesic nerve block, both of which have considerable drawbacks ([ 18 ][16]). Our neuromodulation pain treatment represents a real advance with respect to existing treatments, in that we restore naturalistic percepts, revitalizing the physiological pathway for sensations. Beside the imminent pain relief, this potentially induces beneficial long-term neuroplastic changes at the central nervous system (CNS) level, offering not only an analgesic but also a “curative” effect. As a consequence of the restoration of physiologically plausible sensations, subjects experienced (“embodied”) the prosthesis similar to a real limb. Embodiment is typically measured in “nonfunctional” scenarios [such as rubber-hand experiments ([ 19 ][17])]. We were able to measure an objective functional embodiment ([ 20 ][18]) increase during our experiments with the bionic leg, with and without feedback ([ 15 ][13]). Increased neural embodiment decreased weight perception ([ 11 ][9])—a subjective percept influenced by cognitive processes. Brain cognitive load, measured with electroencephalography, also decreased while walking with the neuroprosthesis and performing a dual task ([ 15 ][13]). ![Figure][19] Different neurotechnologies for the peripheral nervous system (PNS) interfacing Various types of neural electrodes are utilized in individuals with upper- and lower-limb amputation to take input from prosthesis sensors and transduce it into electrical stimulation—restoring sensation from missing appendages. GRAPHIC: C. BICKEL/ SCIENCE BASED ON S. RASPOPOVIC Neuromodulation triggered by a robotic device influences sensorimotor strategies employed by users, by means of its integration into their “traditional” nervous system. To better understand underlying mechanisms, we measured gait features of leg amputees during motor tasks of different difficulty while using the neuroprosthesis. They performed an easy task (walking over ground) and a challenging task (ascending and descending stairs) while gait and neurostimulating parameters were collected. The neuroprosthesis reshaped subjects' legs' kinematics toward a more physiological gait owing to sensorimotor strategies that allowed users to intuitively exploit various features of the neural code during different tasks ([ 21 ][20]). These strategies included different temporal order, or spatial usage of stimulation channels, resulting in simple but robust intuitively integrated neural codes for different motor behaviors. In a hypothetical scenario, which required a leg amputee to simulate driving a conventional car, we demonstrated a finer pressure estimation from the prosthesis, suggesting that even a simple neural code could effectively improve wearable neuromodulating devices. These studies not only provided clear evidence of the benefit of neuromodulation for lower-limb amputees but also provided insights into fundamental mechanisms of supraspinal integration of the restored sensory modalities. Even with only a limited restoration of sensations from foot and knee, the CNS was able to successfully integrate and exploit this information. Analogous findings were observed in animals that compensated for lack of a single sensory modality through supraspinal structures ([ 22 ][21]). The health benefits achievable from neuromodulation are of paramount importance to millions of impaired individuals. Because the economic cost of such technologies remains considerable, it is important to emphasize the accompanying benefits, which could eliminate the need for treatments related to pain or cardiovascular problems ([ 1 ][1]). Together with pioneering results in neuromodulating treatment for neuropathy, the described research presents a conceptually new framework for neuroprosthetic device design, implementation, and testing. This iterative framework consists of (i) developing a deep understanding of the problem through models and experiments, (ii) influencing the device design, and (iii) a meticulously planned clinical testing phase. Multifaceted validation of experiments—including functional, emotional, and cognitive outcomes—feeds back to increase our knowledge and further optimize design. Model-based, deep understanding of the effects of neuromodulation could benefit future projects in the emerging field of bioelectronic medicine ([ 23 ][22], [ 24 ][23]). GRAND PRIZE WINNER Stanisa Raspopovic Stanisa Raspopovic received undergraduate degrees from the University of Pisa and a PhD from Scuola Superiore Sant'Anna, Italy. After completing his postdoctoral fellowship at EPFL, he started his laboratory in the Department of Health Science and Technology at ETH Zürich in 2018. His research focuses on deep understanding of nervous system interaction with electric field through computational modeling, design of sensory neuroprostheses, and bioelectronics solutions and the investigation of human interaction with these. FINALIST Weijian Yang Weijian Yang received his undergraduate degree from Peking University and a PhD from the University of California, Berkeley. After completing his postdoctoral fellowship at Columbia University, he started his laboratory in the Department of Electrical and Computer Engineering at the University of California, Davis in 2017. His research aims to develop advanced optical methods and neurotechnologies to interrogate and modulate brain activity, with a goal to understand how neural circuits organize and function and how behaviors emerge from neuronal activity. [ www.sciencemag.org/content/373/6555/635 ][24] 1. [↵][25]1. S. Raspopovic , Science 370, 290 (2020). [OpenUrl][26][Abstract/FREE Full Text][27] 2. [↵][28]1. S. Raspopovic et al ., Sci. Transl. Med. 6, 222ra19 (2014). [OpenUrl][29][Abstract/FREE Full Text][30] 3. 1. J. A. George et al ., Sci. Robot. 4, eaax2352 (2019). [OpenUrl][31] 4. 1. D. W. Tan et al ., Sci. Transl. Med. 6, 257ra138 (2014). [OpenUrl][32][Abstract/FREE Full Text][33] 5. [↵][34]1. C. M. Oddo et al ., eLife 5, e09148 (2016). [OpenUrl][35][CrossRef][36][PubMed][37] 6. [↵][38]1. M. Ortiz-Catalan et al ., N. Engl. J. Med. 382, 1732 (2020). [OpenUrl][39] 7. [↵][40]1. F. M. Petrini et al ., Ann. Neurol. 85, 137 (2019). [OpenUrl][41][CrossRef][42] 8. [↵][43]1. S. Raspopovic et al ., Nat. Mater. 20, 925 (2021). [OpenUrl][44] 9. [↵][45]1. S. Raspopovic et al ., Proc. IEEE 105, 34 (2017). [OpenUrl][46] 10. [↵][47]1. M. Zelechowski et al ., J. Neuroeng. Rehabil. 17, 24 (2020). [OpenUrl][48] 11. [↵][49]1. G. Preatoni et al ., Curr. Biol. 31, 1065 (2021). [OpenUrl][50] 12. [↵][51]1. L. Nolan et al ., Gait Posture 17, 142 (2003). [OpenUrl][52][CrossRef][53][PubMed][54][Web of Science][55] 13. [↵][56]1. H. Flor , Lancet Neurol. 1, 182 (2002). [OpenUrl][57][CrossRef][58][PubMed][59][Web of Science][60] 14. [↵][61]1. F. M. Petrini et al ., Nat. Med. 25, 1356 (2019). [OpenUrl][62][CrossRef][63][PubMed][64] 15. [↵][65]1. F. M. Petrini et al ., Sci. Transl. Med. 11, eaav8939 (2019). [OpenUrl][66][Abstract/FREE Full Text][67] 16. [↵][68]1. C. Richardson, 2. J. Kulkarni , J. Pain Res. 10, 1861 (2017). [OpenUrl][69] 17. [↵][70]1. K. Kumar et al ., Surg. Neurol. 50, 110, discussion 120 (1998). [OpenUrl][71][CrossRef][72][PubMed][73][Web of Science][74] 18. [↵][75]1. Y. A. Patel, 2. R. J. Butera , J. Neural Eng. 15, 031002 (2018). [OpenUrl][76] 19. [↵][77]1. M. Botvinick, 2. J. Cohen , Nature 391, 756 (1998). [OpenUrl][78][CrossRef][79][PubMed][80][Web of Science][81] 20. [↵][82]1. G. Rognini et al ., J. Neurol. Neurosurg. Psychiatry 90, 833 (2019). [OpenUrl][83][FREE Full Text][84] 21. [↵][85]1. G. Valle et al ., Sci. Adv. 7, eabd8354 (2021). [OpenUrl][86][FREE Full Text][87] 22. [↵][88]1. S. Rossignol et al ., Physiol. Rev. 86, 89 (2006). [OpenUrl][89][CrossRef][90][PubMed][91][Web of Science][92] 23. [↵][93]1. M. A. Hamza et al ., Diabetes Care 23, 365 (2000). [OpenUrl][94][Abstract][95] 24. [↵][96]1. L. V. Borovikova et al ., Nature 405, 458 (2000). [OpenUrl][97][CrossRef][98][PubMed][99][Web of Science][100] [1]: #ref-1 [2]: #ref-2 [3]: #ref-7 [4]: #ref-5 [5]: #ref-6 [6]: #ref-8 [7]: #ref-9 [8]: #ref-10 [9]: #ref-11 [10]: #ref-12 [11]: #ref-13 [12]: #ref-14 [13]: #ref-15 [14]: #ref-16 [15]: #ref-17 [16]: #ref-18 [17]: #ref-19 [18]: #ref-20 [19]: pending:yes [20]: #ref-21 [21]: #ref-22 [22]: #ref-23 [23]: #ref-24 [24]: http://www.sciencemag.org/content/373/6555/635 [25]: #xref-ref-1-1 "View reference 1 in text" [26]: {openurl}?query=rft.jtitle%253DScience%26rft.stitle%253DScience%26rft.aulast%253DRaspopovic%26rft.auinit1%253DS.%26rft.volume%253D370%26rft.issue%253D6514%26rft.spage%253D290%26rft.epage%253D291%26rft.atitle%253DAdvancing%2Blimb%2Bneural%2Bprostheses%26rft_id%253Dinfo%253Adoi%252F10.1126%252Fscience.abb1073%26rft_id%253Dinfo%253Apmid%252F33060348%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [27]: /lookup/ijlink/YTozOntzOjQ6InBhdGgiO3M6MTQ6Ii9sb29rdXAvaWpsaW5rIjtzOjU6InF1ZXJ5IjthOjQ6e3M6ODoibGlua1R5cGUiO3M6NDoiQUJTVCI7czoxMToiam91cm5hbENvZGUiO3M6Mzoic2NpIjtzOjU6InJlc2lkIjtzOjEyOiIzNzAvNjUxNC8yOTAiO3M6NDoiYXRvbSI7czoyMjoiL3NjaS8zNzMvNjU1NS82MzQuYXRvbSI7fXM6ODoiZnJhZ21lbnQiO3M6MDoiIjt9 [28]: #xref-ref-2-1 "View reference 2 in text" [29]: {openurl}?query=rft.jtitle%253DScience%2BTranslational%2BMedicine%26rft.stitle%253DSci%2BTransl%2BMed%26rft.aulast%253DRaspopovic%26rft.auinit1%253DS.%26rft.volume%253D6%26rft.issue%253D222%26rft.spage%253D222ra19%26rft.epage%253D222ra19%26rft.atitle%253DRestoring%2BNatural%2BSensory%2BFeedback%2Bin%2BReal-Time%2BBidirectional%2BHand%2BProstheses%26rft_id%253Dinfo%253Adoi%252F10.1126%252Fscitranslmed.3006820%26rft_id%253Dinfo%253Apmid%252F24500407%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [30]: /lookup/ijlink/YTozOntzOjQ6InBhdGgiO3M6MTQ6Ii9sb29rdXAvaWpsaW5rIjtzOjU6InF1ZXJ5IjthOjQ6e3M6ODoibGlua1R5cGUiO3M6NDoiQUJTVCI7czoxMToiam91cm5hbENvZGUiO3M6MTE6InNjaXRyYW5zbWVkIjtzOjU6InJlc2lkIjtzOjEzOiI2LzIyMi8yMjJyYTE5IjtzOjQ6ImF0b20iO3M6MjI6Ii9zY2kvMzczLzY1NTUvNjM0LmF0b20iO31zOjg6ImZyYWdtZW50IjtzOjA6IiI7fQ== [31]: {openurl}?query=rft.jtitle%253DSci.%2BRobot.%26rft.volume%253D4%26rft.spage%253D2352eaax%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [32]: {openurl}?query=rft.jtitle%253DScience%2BTranslational%2BMedicine%26rft.stitle%253DSci%2BTransl%2BMed%26rft.aulast%253DTan%26rft.auinit1%253DD.%2BW.%26rft.volume%253D6%26rft.issue%253D257%26rft.spage%253D257ra138%26rft.epage%253D257ra138%26rft.atitle%253DA%2Bneural%2Binterface%2Bprovides%2Blong-term%2Bstable%2Bnatural%2Btouch%2Bperception%26rft_id%253Dinfo%253Adoi%252F10.1126%252Fscitranslmed.3008669%26rft_id%253Dinfo%253Apmid%252F25298320%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [33]: /lookup/ijlink/YTozOntzOjQ6InBhdGgiO3M6MTQ6Ii9sb29rdXAvaWpsaW5rIjtzOjU6InF1ZXJ5IjthOjQ6e3M6ODoibGlua1R5cGUiO3M6NDoiQUJTVCI7czoxMToiam91cm5hbENvZGUiO3M6MTE6InNjaXRyYW5zbWVkIjtzOjU6InJlc2lkIjtzOjE0OiI2LzI1Ny8yNTdyYTEzOCI7czo0OiJhdG9tIjtzOjIyOiIvc2NpLzM3My82NTU1LzYzNC5hdG9tIjt9czo4OiJmcmFnbWVudCI7czowOiIiO30= [34]: #xref-ref-5-1 "View reference 5 in text" [35]: {openurl}?query=rft.jtitle%253DeLife%26rft.volume%253D5%26rft.spage%253De09148%26rft_id%253Dinfo%253Adoi%252F10.7554%252FeLife.09148%26rft_id%253Dinfo%253Apmid%252F26952132%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [36]: /lookup/external-ref?access_num=10.7554/eLife.09148&link_type=DOI [37]: /lookup/external-ref?access_num=26952132&link_type=MED&atom=%2Fsci%2F373%2F6555%2F634.atom [38]: #xref-ref-6-1 "View reference 6 in text" [39]: {openurl}?query=rft.jtitle%253DN.%2BEngl.%2BJ.%2BMed.%26rft.volume%253D382%26rft.spage%253D1732%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [40]: #xref-ref-7-1 "View reference 7 in text" [41]: {openurl}?query=rft.jtitle%253DAnn.%2BNeurol.%26rft.volume%253D85%26rft.spage%253D137%26rft_id%253Dinfo%253Adoi%252F10.1002%252Fana.25384%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [42]: /lookup/external-ref?access_num=10.1002/ana.25384&link_type=DOI [43]: #xref-ref-8-1 "View reference 8 in text" [44]: {openurl}?query=rft.jtitle%253DNat.%2BMater.%26rft.volume%253D20%26rft.spage%253D925%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [45]: #xref-ref-9-1 "View reference 9 in text" [46]: {openurl}?query=rft.jtitle%253DProc.%2BIEEE%26rft.volume%253D105%26rft.spage%253D34%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [47]: #xref-ref-10-1 "View reference 10 in text" [48]: {openurl}?query=rft.jtitle%253DJ.%2BNeuroeng.%2BRehabil.%26rft.volume%253D17%26rft.spage%253D24%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [49]: #xref-ref-11-1 "View reference 11 in text" [50]: {openurl}?query=rft.jtitle%253DCurr.%2BBiol.%26rft.volume%253D31%26rft.spage%253D1065%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [51]: #xref-ref-12-1 "View reference 12 in text" [52]: {openurl}?query=rft.jtitle%253DGait%2B%2526%2Bposture%26rft.stitle%253DGait%2BPosture%26rft.aulast%253DNolan%26rft.auinit1%253DL.%26rft.volume%253D17%26rft.issue%253D2%26rft.spage%253D142%26rft.epage%253D151%26rft.atitle%253DAdjustments%2Bin%2Bgait%2Bsymmetry%2Bwith%2Bwalking%2Bspeed%2Bin%2Btrans-femoral%2Band%2Btrans-tibial%2Bamputees.%26rft_id%253Dinfo%253Adoi%252F10.1016%252FS0966-6362%252802%252900066-8%26rft_id%253Dinfo%253Apmid%252F12633775%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [53]: /lookup/external-ref?access_num=10.1016/S0966-6362(02)00066-8&link_type=DOI [54]: /lookup/external-ref?access_num=12633775&link_type=MED&atom=%2Fsci%2F373%2F6555%2F634.atom [55]: /lookup/external-ref?access_num=000181734500008&link_type=ISI [56]: #xref-ref-13-1 "View reference 13 in text" [57]: {openurl}?query=rft.jtitle%253DLancet.%2BNeurology%26rft.stitle%253DLancet%2BNeurol%26rft.aulast%253DFlor%26rft.auinit1%253DH.%26rft.volume%253D1%26rft.issue%253D3%26rft.spage%253D182%26rft.epage%253D189%26rft.atitle%253DPhantom-limb%2Bpain%253A%2Bcharacteristics%252C%2Bcauses%252C%2Band%2Btreatment.%26rft_id%253Dinfo%253Adoi%252F10.1016%252FS1474-4422%252802%252900074-1%26rft_id%253Dinfo%253Apmid%252F12849487%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [58]: /lookup/external-ref?access_num=10.1016/S1474-4422(02)00074-1&link_type=DOI [59]: /lookup/external-ref?access_num=12849487&link_type=MED&atom=%2Fsci%2F373%2F6555%2F634.atom [60]: /lookup/external-ref?access_num=000177695100020&link_type=ISI [61]: #xref-ref-14-1 "View reference 14 in text" [62]: {openurl}?query=rft.jtitle%253DNat.%2BMed.%26rft.volume%253D25%26rft.spage%253D1356%26rft_id%253Dinfo%253Adoi%252F10.1038%252Fs41591-019-0567-3%26rft_id%253Dinfo%253Apmid%252F31501600%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [63]: /lookup/external-ref?access_num=10.1038/s41591-019-0567-3&link_type=DOI [64]: /lookup/external-ref?access_num=31501600&link_type=MED&atom=%2Fsci%2F373%2F6555%2F634.atom [65]: #xref-ref-15-1 "View reference 15 in text" [66]: {openurl}?query=rft.jtitle%253DScience%2BTranslational%2BMedicine%26rft.stitle%253DSci%2BTransl%2BMed%26rft.aulast%253DPetrini%26rft.auinit1%253DF.%2BM.%26rft.volume%253D11%26rft.issue%253D512%26rft.spage%253Deaav8939%26rft.epage%253Deaav8939%26rft.atitle%253DEnhancing%2Bfunctional%2Babilities%2Band%2Bcognitive%2Bintegration%2Bof%2Bthe%2Blower%2Blimb%2Bprosthesis%26rft_id%253Dinfo%253Adoi%252F10.1126%252Fscitranslmed.aav8939%26rft_id%253Dinfo%253Apmid%252F31578244%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [67]: /lookup/ijlink/YTozOntzOjQ6InBhdGgiO3M6MTQ6Ii9sb29rdXAvaWpsaW5rIjtzOjU6InF1ZXJ5IjthOjQ6e3M6ODoibGlua1R5cGUiO3M6NDoiQUJTVCI7czoxMToiam91cm5hbENvZGUiO3M6MTE6InNjaXRyYW5zbWVkIjtzOjU6InJlc2lkIjtzOjE1OiIxMS81MTIvZWFhdjg5MzkiO3M6NDoiYXRvbSI7czoyMjoiL3NjaS8zNzMvNjU1NS82MzQuYXRvbSI7fXM6ODoiZnJhZ21lbnQiO3M6MDoiIjt9 [68]: #xref-ref-16-1 "View reference 16 in text" [69]: {openurl}?query=rft.jtitle%253DJ.%2BPain%2BRes.%26rft.volume%253D10%26rft.spage%253D1861%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [70]: #xref-ref-17-1 "View reference 17 in text" [71]: {openurl}?query=rft.jtitle%253DSurgical%2Bneurology%26rft.stitle%253DSurg%2BNeurol%26rft.aulast%253DKumar%26rft.auinit1%253DK.%26rft.volume%253D50%26rft.issue%253D2%26rft.spage%253D110%26rft.epage%253D120%26rft.atitle%253DEpidural%2Bspinal%2Bcord%2Bstimulation%2Bfor%2Btreatment%2Bof%2Bchronic%2Bpain--some%2Bpredictors%2Bof%2Bsuccess.%2BA%2B15-year%2Bexperience.%26rft_id%253Dinfo%253Adoi%252F10.1016%252FS0090-3019%252898%252900012-3%26rft_id%253Dinfo%253Apmid%252F9701116%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [72]: /lookup/external-ref?access_num=10.1016/S0090-3019(98)00012-3&link_type=DOI [73]: /lookup/external-ref?access_num=9701116&link_type=MED&atom=%2Fsci%2F373%2F6555%2F634.atom [74]: /lookup/external-ref?access_num=000075183100017&link_type=ISI [75]: #xref-ref-18-1 "View reference 18 in text" [76]: {openurl}?query=rft.jtitle%253DJ.%2BNeural%2BEng.%26rft.volume%253D15%26rft.spage%253D031002%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [77]: #xref-ref-19-1 "View reference 19 in text" [78]: {openurl}?query=rft.jtitle%253DNature%26rft.stitle%253DNature%26rft.aulast%253DBotvinick%26rft.auinit1%253DM.%26rft.volume%253D391%26rft.issue%253D6669%26rft.spage%253D756%26rft.epage%253D756%26rft.atitle%253DRubber%2Bhands%2B%2527feel%2527%2Btouch%2Bthat%2Beyes%2Bsee.%26rft_id%253Dinfo%253Adoi%252F10.1038%252F35784%26rft_id%253Dinfo%253Apmid%252F9486643%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [79]: /lookup/external-ref?access_num=10.1038/35784&link_type=DOI [80]: /lookup/external-ref?access_num=9486643&link_type=MED&atom=%2Fsci%2F373%2F6555%2F634.atom [81]: /lookup/external-ref?access_num=000072089500037&link_type=ISI [82]: #xref-ref-20-1 "View reference 20 in text" [83]: {openurl}?query=rft.jtitle%253DJ.%2BNeurol.%2BNeurosurg.%2BPsychiatry%26rft_id%253Dinfo%253Adoi%252F10.1136%252Fjnnp-2018-318570%26rft_id%253Dinfo%253Apmid%252F30100550%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [84]: /lookup/ijlink/YTozOntzOjQ6InBhdGgiO3M6MTQ6Ii9sb29rdXAvaWpsaW5rIjtzOjU6InF1ZXJ5IjthOjQ6e3M6ODoibGlua1R5cGUiO3M6NDoiRlVMTCI7czoxMToiam91cm5hbENvZGUiO3M6NDoiam5ucCI7czo1OiJyZXNpZCI7czo4OiI5MC83LzgzMyI7czo0OiJhdG9tIjtzOjIyOiIvc2NpLzM3My82NTU1LzYzNC5hdG9tIjt9czo4OiJmcmFnbWVudCI7czowOiIiO30= [85]: #xref-ref-21-1 "View reference 21 in text" [86]: {openurl}?query=rft.jtitle%253DScience%2BAdvances%26rft.stitle%253DSci%2BAdv%26rft.aulast%253DValle%26rft.auinit1%253DG.%26rft.volume%253D7%26rft.issue%253D17%26rft.spage%253Deabd8354%26rft.epage%253Deabd8354%26rft.atitle%253DMechanisms%2Bof%2Bneuro-robotic%2Bprosthesis%2Boperation%2Bin%2Bleg%2Bamputees%26rft_id%253Dinfo%253Adoi%252F10.1126%252Fsciadv.abd8354%26rft_id%253Dinfo%253Apmid%252F33883127%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [87]: /lookup/ijlink/YTozOntzOjQ6InBhdGgiO3M6MTQ6Ii9sb29rdXAvaWpsaW5rIjtzOjU6InF1ZXJ5IjthOjQ6e3M6ODoibGlua1R5cGUiO3M6MzoiUERGIjtzOjExOiJqb3VybmFsQ29kZSI7czo4OiJhZHZhbmNlcyI7czo1OiJyZXNpZCI7czoxMzoiNy8xNy9lYWJkODM1NCI7czo0OiJhdG9tIjtzOjIyOiIvc2NpLzM3My82NTU1LzYzNC5hdG9tIjt9czo4OiJmcmFnbWVudCI7czowOiIiO30= [88]: #xref-ref-22-1 "View reference 22 in text" [89]: {openurl}?query=rft.jtitle%253DPhysiological%2BReviews%26rft.stitle%253DPhysiol.%2BRev.%26rft.aulast%253DRossignol%26rft.auinit1%253DS.%26rft.volume%253D86%26rft.issue%253D1%26rft.spage%253D89%26rft.epage%253D154%26rft.atitle%253DDynamic%2BSensorimotor%2BInteractions%2Bin%2BLocomotion%26rft_id%253Dinfo%253Adoi%252F10.1152%252Fphysrev.00028.2005%26rft_id%253Dinfo%253Apmid%252F16371596%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [90]: /lookup/external-ref?access_num=10.1152/physrev.00028.2005&link_type=DOI [91]: /lookup/external-ref?access_num=16371596&link_type=MED&atom=%2Fsci%2F373%2F6555%2F634.atom [92]: /lookup/external-ref?access_num=000234758500003&link_type=ISI [93]: #xref-ref-23-1 "View reference 23 in text" [94]: {openurl}?query=rft.jtitle%253DDiabetes%2BCare%26rft.stitle%253DDiabetes%2BCare%26rft.aulast%253DHamza%26rft.auinit1%253DM.%26rft.volume%253D23%26rft.issue%253D3%26rft.spage%253D365%26rft.epage%253D370%26rft.atitle%253DPercutaneous%2Belectrical%2Bnerve%2Bstimulation%253A%2Ba%2Bnovel%2Banalgesic%2Btherapy%2Bfor%2Bdiabetic%2Bneuropathic%2Bpain%26rft_id%253Dinfo%253Adoi%252F10.2337%252Fdiacare.23.3.365%26rft_id%253Dinfo%253Apmid%252F10868867%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [95]: /lookup/ijlink/YTozOntzOjQ6InBhdGgiO3M6MTQ6Ii9sb29rdXAvaWpsaW5rIjtzOjU6InF1ZXJ5IjthOjQ6e3M6ODoibGlua1R5cGUiO3M6NDoiQUJTVCI7czoxMToiam91cm5hbENvZGUiO3M6NzoiZGlhY2FyZSI7czo1OiJyZXNpZCI7czo4OiIyMy8zLzM2NSI7czo0OiJhdG9tIjtzOjIyOiIvc2NpLzM3My82NTU1LzYzNC5hdG9tIjt9czo4OiJmcmFnbWVudCI7czowOiIiO30= [96]: #xref-ref-24-1 "View reference 24 in text" [97]: {openurl}?query=rft.jtitle%253DNature%26rft.stitle%253DNature%26rft.aulast%253DBorovikova%26rft.auinit1%253DL.%2BV.%26rft.volume%253D405%26rft.issue%253D6785%26rft.spage%253D458%26rft.epage%253D462%26rft.atitle%253DVagus%2Bnerve%2Bstimulation%2Battenuates%2Bthe%2Bsystemic%2Binflammatory%2Bresponse%2Bto%2Bendotoxin.%26rft_id%253Dinfo%253Adoi%252F10.1038%252F35013070%26rft_id%253Dinfo%253Apmid%252F10839541%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [98]: /lookup/external-ref?access_num=10.1038/35013070&link_type=DOI [99]: /lookup/external-ref?access_num=10839541&link_type=MED&atom=%2Fsci%2F373%2F6555%2F634.atom [100]: /lookup/external-ref?access_num=000087212000049&link_type=ISI

Opendoor's Sam Stone discusses machine learning algorithms in real estate industry and how data science is used to assess property values.

I have been asked this question a few times so I have decided to write this post about the current services of Livepeer and the future implementations Livepeer could bring to the decentralized world. This may be helpful for new comers that want to learn about Livepeer and have an idea of where Livepeer could take us in the future. But first we need to cover some important topics of where we are right now. First, let's look at the difference between Ethereum Mining and Video Mining. Livepeer has many possible services it could provide.

Science is a catalyst for human progress. But a publishing monopoly and funding monopsony have inhibited research. We intend to improve incentives in science by developing smart research contracts. These will collectively reward scientific activities, including proposals, papers, replications, datasets, analyses, annotations, editorials, and more. Peer-to-peer review networks will be designed to help evaluate proposals and publications. Long term, these smart contracts help accelerate research by minimizing science friction, ensuring science quality, and maximizing science variance. Email bits@atoms.org or follow @atoms_org to help us build a flourishing research economy. Papers are the fundamental asset of the research economy: they serve as proof of work that valuable research has been completed. Funding agencies and research institutions evaluate scientists based on their publications. Principal investigators (PIs) attract prospective students and collaborators via papers. Investors and companies use scientific literature to conduct due diligence on research ranging from basic discoveries to clinical studies. Thus, the evaluation and dissemination of papers are vital to this research economy. Publishers are the sole arbiters of papers today. They assign a value -- denominated in "prestige" -- by accepting a paper into the appropriate journal based on selectivity and domain. To evaluate papers, journals typically outsource it to two or three PIs, who often outsource it further to their students. Reviewers are unpaid for this peer review work, as it is an expected part of their scientific duties. Peer review is believed to be necessary because of the industrialization of science. Research papers and proposals have become too specialized and too numerous, making it difficult to assess merit prima facie. As a result, scientific incentives have become distorted in two major ways: prestige capture and reviewer misalignment. Over half of all research papers in 2013 were published by five companies, who have used their centuries of brand equity to build an economic moat. This results in prestige capture, which akin to regulatory capture, causes public and scientific interest to be directed towards the regulators of prestige.

When it comes to hiring, it's increasingly becoming an AI's world--we're just working in it. In this, the final episode of Season 2 of our AI podcast "In Machines We Trust" and the conclusion of our series on AI and hiring, we take a look at how AI-based systems are increasingly playing gatekeeper in the hiring process--screening out applicants by the millions, based on little more than what they see in your résumé. In fact, an increasing number of people and services are designed to help you play by--and in some cases bend--their rules to give you an edge. This is NOT Jennifer Strong. To wrap up our hiring series, the two of us took turns doing the same job interview, because she was curious if the automated interviewer would notice. So, human Jennifer beat me as a better match for the job posting, but just by a little bit. It got better personality scores. Because, according to this hiring software, this fake voice is more spontaneous. It also got ranked as more innovative and strategic, while Jennifer is more passionate, and she's better at working with others. Jennifer: Artificial intelligence is increasingly used in the hiring process. And these days algorithms decide whether a resume gets seen by a human, gauge personalities based on how people talk or play video games, and might even interview you. In a world where you no longer prepare for those interviews by putting your best foot forward--what does it mean to present your best digital self? Sot: Youtube clips montage: Vlogger 1: Want to know three easy hacks to significantly improve your performance on video interviews like HireVue, Spark Hire, or VidCruiter? Vlogger 2: Please do make sure you watch this from beginning to end, because I want to help you to pass your interview.

In the young discipline of robotics-inspired biology, robots replace experimental animals, allowing researchers to learn about animals under a wider range of conditions than exist in nature or the laboratory. What is the secret behind the steady but oh-so-elegant way in which cats move? That's the subject of a study in Frontiers in Neurorobotics by scientists from Osaka University, who built a novel, 47cm-long and 7.6kg-heavy robotic cat. Based on previous research on the gait of real domestic cats, the authors deduced that key to the cats' sleek movement must lie in a previously unknown reflex circuit, which they call the "reciprocal excitatory circuit between hip and knee extensors". According to their hypothesis, this reflex circuit has two essential features.

I recently started an AI-focused educational newsletter, that already has over 80,000 subscribers. TheSequence is a no-BS (meaning no hype, no news etc) ML-oriented newsletter that takes 5 minutes to read. The goal is to keep you up to date with machine learning projects, research papers and concepts. Recently, one of my students asked me a question as of whether DeepMind was solely working in reinforcement learning applications. The answer is obviously no but the question is still valid as it rooted in the fact that most of DeepMind's highly publicized work such as AlphaGo, MuZero or AlphaFold are based in reinforcement learning.

And this overhead is relatively large, so it's estimated that you need a few 100 to 1000 physical qubits to get to one logical qubit. And then this logical qubit has a significantly suppressed error. And then you can start to work with that, in this clean theoretic computational paradigm where you ignore more or less the noise from the hardware.

All the sessions from Transform 2021 are available on-demand now. As part of VentureBeat's series of interviews with women and BIPOC leaders in the AI industry, we sat down with Dr. Katia Walsh, chief strategy and artificial intelligence officer, Levi Strauss & Co. In her career she has forged paths for people from every intersection of race, culture, class, and education, giving them the tools they need in an AI- and data-centric world to be creative, solve problems, develop new solutions, and change the game in their roles across their companies. VB: Could you tell us about your background, and your current role at your company? I started my career as a journalist in communist Bulgaria, where I personally experienced the power of information through a story I wrote while still in high school.