The movie business has the Oscars, and the music business has the Grammys, so the podcast business needs its personal awards present. A gaggle of business leaders spanning networks, together with from Spotify, NPR, Wondery, and Sony Music, introduced immediately that they plan to launch a brand new awards present: the Golden Mics. The group has additionally shaped the Podcast Academy, a membership-driven not-for-profit group whose members will vote on Golden Mics winners. The group says it’ll begin accepting functions this spring, and the primary present can be in Los Angeles subsequent 12 months.
As extra firms spend money on their very own reveals, notably long-form narrative programming, creators need recognition for his or her work — understandably. A podcast awards present is smart, though it’d present creators with a bragging level greater than outsized consideration. Technically, a podcast awards present already exists: iHeartRadio launched its personal awards present in 2019 as a approach to honor high quality reveals, however individuals within the business discovered it fishy that the community nominated its personal reveals for awards and subsequently gained them. These new awards are clearly a rejection of that concept, and nobody from iHeart is a Podcast Academy founding member.
However a brand new awards present launch doesn’t imply individuals will routinely care or respect them. The Oscars, Grammys, and Golden Globes are well-known (and, within the Oscars’ case, practically 100 years previous). Audiences already revere them. Plus, they arrive with the spectacle of well-known movie star hosts and musical acts.
The podcasting business is totally different. There aren’t many well-known names that would draw a crowd, and in contrast to music, movie, or TV, most publications don’t make use of official podcast reviewers. The press machine isn’t well-oiled for podcast protection. Discovering reveals might be troublesome, too, with out many tastemakers within the area.
The Golden Mics might be a chance to name consideration to the most effective of audio, or it’d find yourself simply giving reveals an opportunity to ship out a press launch within the hopes that folks listen. Beginning an awards present is a primary step to bringing extra status and press to the business, however the remainder of the media machine has to work in tandem for the awards to seize extra of individuals’s time and respect.
Facebook’s AI speeds up natural language processing without additional training
Pure language fashions sometimes have to unravel two powerful issues: mapping sentence prefixes to fixed-sized representations and utilizing the representations to foretell the following phrase within the textual content. In a current paper, researchers at Fb AI Analysis assert that the primary drawback — the mapping drawback — is likely to be simpler than the prediction drawback, a speculation they construct upon to enhance language fashions with a “nearest neighbors” retrieval mechanism. They are saying it permits uncommon patterns to be memorized and that it achieves a state-of-the-art complexity rating (a measure of vocabulary and syntax selection) with no further coaching.
Because the researchers clarify, language fashions assign possibilities to sequences of phrases, such that from a context sequence of tokens (e.g., phrases) they estimate the distribution (the possibilities of prevalence of various potential outcomes) over goal tokens. The proposed strategy — kNN-LM — maps a context to a fixed-length mathematical illustration computed by the pre-trained language mannequin. Given a coaching instance, a key-value pair is outlined, the place the secret is the mathematical illustration of the context and the worth is the goal phrase.
At take a look at time, kNN-LM takes an enter context and generates an output distribution over subsequent phrases and the context illustration. It retrieves its nearest neighbors in accordance with a distance perform, at which level it computes a distribution over neighbors whereas aggregating possibilities for every vocabulary merchandise throughout all its occurrences within the retrieved targets.
The researchers notice that kNN-LM is appropriate with any language mannequin that produces fixed-size context representations. Within the examine, this enabled the coaching of a Transformer-based mannequin on a knowledge set consisting of 103 million tokens from Wikipedia articles, 250,000 of which had been reserved for growth and testing.
In experiments, the kNN-LM “considerably” outperformed the baselines at take a look at time, which the crew attributes to its propensity for studying a illustration perform for contexts with an implicit notion of similarity. The kNN-LM added some computational overhead — it took roughly two hours on a single processor to construct a cache for 103 million entries, and operating the validation set took roughly 25 minutes. However the crew factors out that it’s “trivial” to parallelize the mannequin and that it requires no GPU-based coaching.
“Generally, we discover that examples the place kNN-LM is most useful sometimes include uncommon patterns,” the coauthors of the examine wrote. “Examples embody factual information, names, and near-duplicate sentences from the coaching set. In these instances, assigning prepare and take a look at situations related representations … seems to be a neater drawback than implicitly memorizing the following phrase in mannequin parameters.”
Democratic debate memes: Warren and Sanders show Mike Bloomberg absolutely no mercy
This story is part of , CNET’s full coverage of the 2020 elections.
One otherkicked off Wednesday evening in Las Vegas with Joe Biden, Pete Buttigieg, Amy Klobuchar, Bernie Sanders, Elizabeth Warren and a debate newcomer, former NYC mayor Mike Bloomberg, who took a lot of warmth.
Twitter had loads to say in regards to the showdown.
Warren comes out swinging
The controversy began off with abs proper off the bat with Warren reminding the viewers that President Donald Trump is not the one one who has used misogynic phrases towards girls, however that Bloomberg is responsible of the identical tactic. Bloomberg has struggled to recuperate ever since. Twitter customers responded with reactions exhibiting all the things from Rocky boxing to Pokemon creatures respiratory fireplace.
And uh… Sport of Thrones.
This may be the perfect use of the “Curb your Enthusiasm” meme I’ve seen shortly…
Submit-it Notes vs. PowerPoint
Warren additionally geared toward Buttigieg’s well being care plan, calling it a PowerPoint as a substitute of an actual plan and mentioned Klobuchar’s is simply “a Submit-it Notice.” And Twitter had enjoyable with memes of Submit-its and references to the 1997 film Romy and Michele’s Excessive College Reunion, during which the primary characters faux to be the true inventors of the favored sticky notepad.
Bloomberg will get dragged
Bloomberg bought attacked by all sides about his taxes, mistreatment of ladies and assist of racial profiling, resulting in memes exhibiting group fights and animated GIFs of The Workplace’s Michael Scott trying further agitated.
This one may sum it up finest.
Tough evening for Bloomberg.
Initially revealed Feb. 19 at 6:55 p.m. PT and up to date all through the occasion.