Ai Writes Inspirational Quotes

Bisognerebbe saper attendere, raccogliere, per una vita intera e possibilmente lunga, senso e dolcezza, e poi, proprio alla fine, si potrebbero forse scrivere dieci righe valide. Perché i versi non sono, come crede la gente, sentimenti (che si acquistano precocemente), sono esperienze. Per scrivere un verso bisogna vedere molte città, uomini e cose, bisogna conoscere gli animali, bisogna capire il volo degli uccelli e comprendere il gesto con cui i piccoli fiori si aprono al mattino. Bisogna saper ripensare a itinerari in regioni sconosciute, a incontri inaspettati e congedi previsti da tempo, a giorni dell'infanzia ancora indecifrati, ai genitori che eravamo costretti a ferire quando portavano una gioia e non la comprendevamo (era una gioia per qualcun altro), a malattie infantili che cominciavano in modo così strano con tante profonde e grevi trasformazioni, a giorni in stanze silenziose e raccolte e a mattine sul mare, al mare sopratutto, a mari, a notti di viaggio che passavano con un alto fruscio e volavano assieme alle stelle - e ancora non è sufficiente poter pensare a tutto questo. Bisogna avere ricordi di molte notti d'amore, nessuna uguale all'altra, di grida di partorienti e di lievi, bianche puerpere addormentate che si rimarginano. Ma bisogna anche essere stati accanto ad agonizzanti, bisogna essere rimasti vicino ai morti nella stanza con la finestra aperta e i rumori intermittenti. E non basta ancora avere ricordi. Bisogna saperli dimenticare, quando sono troppi, e avere la grande pazienza di attendere che ritornino. Perché i ricordi in sé ancora non sono. Solo quando diventano sangue in noi, sguardo e gesto, anonimi e non più distinguibili da noi stessi, soltanto allora può accadere che in un momento eccezionale si levi dal loro centro e sgorghi la prima parola di un verso.

When I launched my AI career in 1983, I did so by waxing philosophic in my application to the Ph.D. program at Carnegie Mellon. I described AI as “the quantification of the human thinking process, the explication of human behavior,” and our “final step” to understanding ourselves. It was a succinct distillation of the romantic notions in the field at that time and one that inspired me as I pushed the bounds of AI capabilities and human knowledge. Today, thirty-five years older and hopefully a bit wiser, I see things differently. The AI programs that we’ve created have proven capable of mimicking and surpassing human brains at many tasks. As a researcher and scientist, I’m proud of these accomplishments. But if the original goal was to truly understand myself and other human beings, then these decades of “progress” got me nowhere. In effect, I got my sense of anatomy mixed up. Instead of seeking to outperform the human brain, I should have sought to understand the human heart. It’s a lesson that it took me far too long to learn. I have spent much of my adult life obsessively working to optimize my impact, to turn my brain into a finely tuned algorithm for maximizing my own influence. I bounced between countries and worked across time zones for that purpose, never realizing that something far more meaningful and far more human lay in the hearts of the family members, friends, and loved ones who surrounded me. It took a cancer diagnosis and the unselfish love of my family for me to finally connect all these dots into a clearer picture of what separates us from the machines we build. That process changed my life, and in a roundabout way has led me back to my original goal of using AI to reveal our nature as human beings. If AI ever allows us to truly understand ourselves, it will not be because these algorithms captured the mechanical essence of the human mind. It will be because they liberated us to forget about optimizations and to instead focus on what truly makes us human: loving and being loved. Reaching that point will require hard work and conscious choices by all of us. Luckily, as human beings, we possess the free will to choose our own goals that AI still lacks. We can choose to come together, working across class boundaries and national borders to write our own ending to the AI story. Let us choose to let machines be machines, and let humans be humans. Let us choose to simply use our machines, and more importantly, to love one another.

Blockchain can be described as “a “write only” digital platform that records and verifies transactions”. Simply put, blockchain is the next step within database development. It can also be called Distributed Ledger Technology (DLT). As a distributed ledger, it is designed and built with the goal of securely storing millions of data within its platform, leveraging a series of architecture tweaks for it. A blockchain is then, nothing else than a database made up of rows, columns, and tables. What differentiates it from other databases, is its sophisticated encryption, that makes it safer, transparent, and more trustworthy. Blockchain technology uses cryptography and digital signatures to prove identity, authenticity, and enforce read/write access rights. All transactions within a block which is part of the blockchain are visible; so there is full transparency for every transaction. What is more, once an entry goes into a blockchain ledger, it cannot be (easily) altered or erased. There is no “central power” overseeing the ledger of transactions. Instead, blockchain technology enables a decentralised and distributed ledger where transactions are shared among a network of computers—in almost real time—rather than being stored on a central server with a central authority (like a bank) overseeing transactions. A blockchain platform is formed out of infinite blocks. The system was inspired by the way bitcoin was first designed when invented in 2008. Similarly to bitcoin, every time a block is made, it will attach itself to the blockchain carrying along a “hash”, or fingerprint from the previous block. These have an important function as they use cryptography to authenticate the source of the transaction.