UPDATE: chapter one is out !!!
Mood board for an upcoming fic I've been working on for a bit. I've always loved the wolf from MM1 so we gonna use him;)..
Supposed be something like Big Bad Wolf! Steve x Reader, was thinking about incorporating Steddie x reader into it so it could also be Big Bad Wolf! Eddie. Though I think I want it to be its own one-shot so I can write a full Steve Harrington fic. We'll see how it rolls out, chapter 1 coming soon;).
Incase we ever bring Eddie in ,(maybe his own fic alone too)
101 notes
·
View notes
You have one book to introduce someone to the series, but can give them a brief summary of relevant background information beforehand. Which do you choose? Ideally I’d like a book which is a microcosm of the series as a whole and highly representative, without too much context required (no starting at 52), and balancing out early-installment weirdness and deus ex machinas. Books I’m thinking of: 1, 7, 8, 19, 25, MM3, or 38 come to mind, but they each have their own strengths and weaknesses
Megamorphs 1: The Andalite's Gift
It introduces all the characters' voices, including how much the rotating first-person point of view adds to the complexity of the story. (Holy persimmons the scene where the veleek takes Marco, as told by Rachel and then Cassie and then Marco himself.)
There's great character development in relatively little space — the bulk of it goes to Cassie's arc with realizing she sometimes has her friends' lives in her hands, choosing wrong when Marco's life is on the line, learning to live with it, and then finding a way to redeem herself. But we also have Tobias dropping in the fact that he and Ax are now BFFs and that he understands Ax was in a survival situation even before the veleek. We have Rachel sort of reinventing the concept of Animorph from the ground up.
"Do you hate trash cans? Is that it? Do you just HATE TRASH CANS?"
... paired with Jake and Cassie going home to cry themselves to sleep that night, because they got Rachel back but are pretty sure they lost Ax and Marco in the process.
"Real mice don't chase people.... At least, I think they don't."
The sequence where Cassie defeats the veleek is about as nifty as the series gets. There's a reason #24 and #34 and #39 all do homages to that scene, because the imagery is so dang cool.
Marco announcing he's not dead by randomly popping up in Jake's bed at 7:00 in the morning.
It introduces a bunch of motifs for the story: whales, inexplicable yeerk logic, Marco's "driving", quirky one-off characters, Ax as crouching straightman hidden troll, Air Tobias, controllers lying to senior leadership, sweet moments of the kids just being kids, graphic descriptions of severed limbs.
You don't need much, if any, background to enjoy it. The books always have exposition at the beginning, and this one's a contained story by design. Yes, it adds something to read MM1 just after #7 and realize that shoe lady ("Frannie") is no longer a controller because Rachel destroyed the kandrona emitter, an action that Rachel herself said she didn't know would make any difference to anyone at all. But you don't need that context; it just adds a drop of dramatic irony to one particular scene.
114 notes
·
View notes
Omg, Max and Marc being teammates in that Honda Thanks Day karting race and they won!!!! Like, of course they won but still, both of them, together!!!! Also Max maxsplaining to Marc might be my new favorite thing
let's fucking goooooo my little champions 🏆
9 notes
·
View notes
Apple’s MM1 Model Brings Multimodal AI to the Forefront
MM1 Method
ReALM (Reference Resolution as Language Modelling), an artificial intelligence system and A novel approach to training large language models (LLMs) that smoothly combines textual and visual data has been created by Apple researchers, attempts to significantly improve the comprehension and response times of voice assistants.
The company’s research results, which are presented in a paper titled MM1 Methods, Analysis & Insights from Multimodal LLM Pre-training,” provide a novel strategy for developing artificial intelligence (AI) systems that are more flexible and clever. Apple claims that the MM1 model sets a new standard in AI’s ability to perform tasks like image captioning, visual question answering, and natural language inference with a high degree of accuracy by using a diverse dataset that includes image-caption pairs, interleaved image-text documents, and text-only data.
MM1 Model
Apple’s research focuses on the fusion of several model architectures and training data sources, allowing the AI to comprehend and produce words based on a mixture of verbal and visual inputs. This capacity is essential for jobs requiring a sophisticated understanding of the outside world, such deciphering complicated visuals or providing answers to queries with visual components.
The remarkable in-context learning capabilities of the MM1 model are also highlighted in the research, especially when the model is in its maximum 30 billion parameter configuration. Using few-shot “chain-of-thought” prompting, this version reportedly demonstrates impressive multi-step reasoning skills across several photos. This method enables the AI to do complicated, open-ended issue solving based on minimum instances.
Apple ReALM Technology
Apple presents a new framework for large language models to handle reference resolution, which includes recognising background and conversational context in addition to interpreting unclear references to on-screen objects. ReALM may thus result in more logical and organic interactions with technology.
Reference resolution, which allows people to utilise pronouns and other indirect references in conversation without becoming confused, is a crucial component of natural language comprehension. This skill has always been a big difficulty for digital assistants, as they have to comprehend a lot of different spoken signals and visual clues. In an attempt to tackle this, Apple’s ReALM technology reduces the difficult task of reference resolution to a pure language modelling issue. By doing this, it is able to interpret allusions to visual components that are shown on a screen and incorporate this comprehension into the dialogue.
ReALM uses linguistic representations to recreate a screen’s visual layout. To do this, on-screen objects and their positions must be parsed in order to produce a text format that accurately represents the structure and content of the screen. Researchers at Apple discovered that this approach, when paired with particular language model fine-tuning for reference resolution tasks, performs noticeably better than conventional techniques, including OpenAI’s GPT-4’s capabilities.
With reference to what is now shown on their screen, ReALM might make it possible for users to engage with digital assistants considerably more effectively without requiring explicit, comprehensive instructions. This might greatly increase the use of voice assistants in a number of contexts, such guiding drivers through infotainment systems while driving or aiding those with impairments by offering a simpler and more precise way to communicate indirectly.
ReALM, an acronym for Reference Resolution as Language Modelling, was introduced by Apple lately. It’s a new approach that aims to greatly enhance the comprehension and response time of virtual assistants such as Siri.
This is the essence of ReALM
Focuses on reference resolution: This is the capacity of the AI to comprehend your meaning when you use ambiguous language, particularly during a conversation. Say “increase the brightness of that,” for example, and ReALM would interpret “that” as referring to the part of the screen you are presently dealing with.
Enhances contextual comprehension: ReALM does more than only translate references. It may deliver a more meaningful and natural answer by considering the context of the discussion as well as what’s occurring on the screen of your device.
Makes Siri smarter: ReALM has the potential to greatly increase the intuitiveness and helpfulness of Siri (as well as maybe other Apple AI helpers) by enhancing these features.
According to Apple, ReALM performs better at managing reference resolution than other big language models like GPT-4.
Although this technology is still in the research stage, it may find its way into next Apple products and services.
ReALM is a promising development in AI that has the potential to completely change how people interact with their gadgets.
This study is a component of Apple’s larger endeavour to improve its AI skills in the face of intensifying competition. According to a story earlier today by Mark Gurman of Bloomberg, Apple and Google are in talks to licence Google’s Gemini generative large-language models for use in iOS 18, which will include new capabilities for the iPhone.
Currently, Apple has released a number of AI research studies. The business unveiled a new technique last month that smoothly combines textual and visual data for training massive language models. It is generally anticipated that Apple will reveal a number of AI capabilities at WWDC in June.
Read more on Govindhtech.com
0 notes