Prepare for a radical acceleration in technological development. A Google Deepmind AI has achieved “an order-of-magnitude expansion in stable materials known to humanity,” finding about 800 years’ worth of new materials with revolutionary potential.
The discovery of new materials with unusual properties can start technological snowballs rolling that eventually push society in new directions – but up to this point, it’s been a painstakingly slow process involving a lot of trial-and-error experimentation.
Inorganic crystal materials, for example, may show enormous promise once you first synthesize them, but all this potential could lead nowhere if the crystals don’t remain stable; it’s no good discovering that a new crystal could improve the performance of batteries or electronics if it’s going to fall apart and degrade.
There has been a sharp uptick in crimes specifically targeting Muslim and Jewish people since the war between Israel and Hamas broke out in October 2023.
Google has revealed “Gemini”, which it says is its largest science and engineering project ever.
It is also the company’s latest attempt to catch up with rival OpenAI to develop artificial intelligence, and try and build a better system than its ChatGPT.
As such, Gemini will come to Google’s Bard, the chatbot that it released in the wake of ChatGPT in an attempt to catch up. But it will also roll out to Google’s Pixels phones and elsewhere.
Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
Last week, a team of researchers from the University of California, Berkeley published a highly anticipated paper in the journal Nature describing an “autonomous laboratory” or “A-Lab” that aimed to use artificial intelligence (AI) and robotics to accelerate the discovery and synthesis of new materials.
Dubbed a “self-driving lab,” the A-Lab presented an ambitious vision of what an AI-powered system could achieve in scientific research when equipped with the latest techniques in computational modeling, machine learning (ML), automation and natural language processing.
It is already disorienting enough to accept that our attention only absorbs a fraction of the events and phenomena unfolding within and around us at any given moment. Now consider that our memory only retains a fraction of what we have attended to in moments past. In the act of recollection, we take these fragments of fragments and try to reconstruct from them a totality of a remembered reality, playing out in the theater of the mind — a stage on which, as neuroscientist Antonio Damasio has observed in his landmark work on consciousness, we often “use our minds not to discover facts, but to hide them.”
We do this on the personal level — out of such selective memory and by such exquisite exclusion, we compose the narrative that is the psychological pillar of our identity. We do it on the cultural level — what we call history is a collective selective memory that excludes far more of the past’s realities than it includes. Borges captured this with his characteristic poetic-philosophical precision when he observed that “we are our memory… that chimerical museum of shifting shapes, that pile of broken mirrors.” To be aware of memory’s chimera is to recognize the slippery, shape-shifting nature of even those truths we think we are grasping most firmly.
Nearly a century after Nietzsche admonished that what we call truth is https://www.themarginalian.org/2018/03/26/nietzsche-on-truth…ral-sense/ the great Japanese filmmaker Akira Kurosawa (March 23, 1910–September 6, 1998) created an exquisite cinematic metaphor for the slippery memory-mediated nature of truth in his 1950 film Rashomon, based on Ryunosuke Akutagawa’s short story “In a Grove” — a psychological-philosophical thriller about the murder of a samurai and its four witnesses, who each recount a radically different reality, each equally believable, thus undermining our most elemental trust in truth.
