Bernard Williams thought that philosophy should address real human concerns felt beyond academic philosophy. But what wider concerns are addressed by Ethics and the Limits of Philosophy, a book he introduces as being ‘principally about how things are in moral philosophy’? In this article, we argue that Williams responded to the concerns of his day indirectly, refraining from explicitly claiming wider cultural relevance, but hinting at it in the pair of epigraphs that opens the main text. This was Williams’s solution (...) to what he perceived as the stylistic problem of how to pursue philosophy as cultural critique. Taking the epigraphs as interpretative keys to the wider resonances of the book, we show how they reveal Williams’s philosophical concerns – with the primacy of character over method, the obligation to follow orders, and the possibility of combining truth, truthfulness, and a meaningful life in a disillusioned world – to be recognisably rooted in the cultural concerns of post-war Britain. In the light of its epigraphs, the book emerges as the critique of a philosophical tradition’s inadequacies to the special difficulties of its cultural moment. (shrink)

This chapter argues that several aspects of Bernard Williams’s style, methodology, and metaphilosophy can be read as evolving dialectically out of Wittgenstein’s own. After considering Wittgenstein as a stylistic influence on Williams, especially as regards ideals of clarity, precision, and depth, Williams’s methodological debt to Wittgenstein is examined, in particular his anthropological interest in thick concepts and their point. The chapter then turns to Williams’s explicit association, in the 1990s, with a certain form of Wittgensteinianism, which he called ‘Left Wittgensteinianism’. (...) It is shown how this is not a sudden conversion, but the direct product of Williams’s longstanding critical engagement with Wittgenstein’s methodology and metaphilosophy: Williams arrives at this position by envisaging a Wittgensteinianism that thinks in concrete sociohistorical terms, embraces genuine explanation, and relinquishes its insistence on the purity of philosophy. When properly understood, moreover, this critique turns out to be continuous with Williams’s advocacy of a conception of philosophy as a humanistic discipline. Finally, it is shown that Williams inherits from Wittgenstein a certain understanding of how philosophy can help us to live, in particular the therapeutic ambition to liberate us from distortions in our self-understanding by assembling reminders. (shrink)

Broadening access to both computational and educational resources is crit- ical to diffusing machine learning (ML) innovation. However, today, most ML resources and experts are siloed in a few countries and organizations. In this article, we describe our pedagogical approach to increasing access to applied ML through a massive open online course (MOOC) on Tiny Machine Learning (TinyML). We suggest that TinyML, applied ML on resource-constrained embedded devices, is an attractive means to widen access because TinyML leverages low-cost and globally (...) accessible hardware and encourages the development of complete, self-contained applications, from data collection to deployment. To this end, a collaboration between academia and industry produced a four part MOOC that provides application-oriented instruction on how to develop solutions using TinyML. The series is openly available on the edX MOOC platform, has no prerequisites beyond basic programming, and is designed for global learners from a variety of backgrounds. It introduces real-world applications, ML algorithms, data-set engineering, and the ethi- cal considerations of these technologies through hands-on programming and deployment of TinyML applications in both the cloud and on their own microcontrollers. To facili- tate continued learning, community building, and collaboration beyond the courses, we launched a standalone website, a forum, a chat, and an optional course-project com- petition. We also open-sourced the course materials, hoping they will inspire the next generation of ML practitioners and educators and further broaden access to cutting-edge ML technologies. (shrink)