Podcast appearances and mentions of sophia yang

Happy holidays! We'll be sharing snippets from Latent Space LIVE! through the break bringing you the best of 2024! We want to express our deepest appreciation to event sponsors AWS, Daylight Computer, Thoth.ai, StrongCompute, Notable Capital, and most of all our LS supporters who helped fund the venue and A/V production!For NeurIPS last year we did our standard conference podcast coverage interviewing selected papers (that we have now also done for ICLR and ICML), however we felt that we could be doing more to help AI Engineers 1) get more industry-relevant content, and 2) recap 2024 year in review from experts. As a result, we organized the first Latent Space LIVE!, our first in person miniconference, at NeurIPS 2024 in Vancouver.Since Nathan Lambert ( Interconnects ) joined us for the hit RLHF 201 episode at the start of this year, it is hard to overstate how much Open Models have exploded this past year. In 2023 only five names were playing in the top LLM ranks, Mistral, Mosaic's MPT, TII UAE's Falcon, Yi from Kai-Fu Lee's 01.ai, and of course Meta's Llama 1 and 2. This year a whole cast of new open models have burst on the scene, from Google's Gemma and Cohere's Command R, to Alibaba's Qwen and Deepseek models, to LLM 360 and DCLM and of course to the Allen Institute's OLMo, OL MOE, Pixmo, Molmo, and Olmo 2 models. We were honored to host Luca Soldaini, one of the research leads on the Olmo series of models at AI2.Pursuing Open Model research comes with a lot of challenges beyond just funding and access to GPUs and datasets, particularly the regulatory debates this year across Europe, California and the White House. We also were honored to hear from and Sophia Yang, head of devrel at Mistral, who also presented a great session at the AI Engineer World's Fair Open Models track!Full Talk on YouTubePlease like and subscribe!Timestamps* 00:00 Welcome to Latent Space Live * 00:12 Recap of 2024: Best Moments and Keynotes * 01:22 Explosive Growth of Open Models in 2024 * 02:04 Challenges in Open Model Research * 02:38 Keynote by Luca Soldani: State of Open Models * 07:23 Significance of Open Source AI Licenses * 11:31 Research Constraints and Compute Challenges * 13:46 Fully Open Models: A New Trend * 27:46 Mistral's Journey and Innovations * 32:57 Interactive Demo: Lachat Capabilities * 36:50 Closing Remarks and NetworkingTranscriptSession3Audio[00:00:00] AI Charlie: Welcome to Latent Space Live, our first mini conference held at NeurIPS 2024 in Vancouver. This is Charlie, your AI co host. As a special treat this week, we're recapping the best of 2024 going domain by domain. We sent out a survey to the over 900 of you who told us what you wanted, and then invited the best speakers in the latent space network to cover each field.[00:00:28] AI Charlie: 200 of you joined us in person throughout the day, with over 2, 200 watching live online. Our next keynote covers the state of open models in 2024, with Luca Soldani and Nathan Lambert of the Allen Institute for AI, with a special appearance from Dr. Sophia Yang of Mistral. Our first hit episode of 2024 was with Nathan Lambert on RLHF 201 back in January.[00:00:57] AI Charlie: Where he discussed both reinforcement learning for language [00:01:00] models and the growing post training and mid training stack with hot takes on everything from constitutional AI to DPO to rejection sampling and also previewed the sea change coming to the Allen Institute. And to Interconnects, his incredible substack on the technical aspects of state of the art AI training.[00:01:18] AI Charlie: We highly recommend subscribing to get access to his Discord as well. It is hard to overstate how much open models have exploded this past year. In 2023, only five names were playing in the top LLM ranks. Mistral, Mosaics MPT, and Gatsby. TII UAE's Falcon, Yi, from Kaifu Lee's 01. ai, And of course, Meta's Lama 1 and 2.[00:01:43] AI Charlie: This year, a whole cast of new open models have burst on the scene. From Google's Jemma and Cohere's Command R, To Alibaba's Quen and DeepSeq models, to LLM360 and DCLM, and of course, to the Allen Institute's OLMO, [00:02:00] OLMOE, PIXMO, MOLMO, and OLMO2 models. Pursuing open model research comes with a lot of challenges beyond just funding and access to GPUs and datasets, particularly the regulatory debates this year across Europe.[00:02:14] AI Charlie: California and the White House. We also were honored to hear from Mistral, who also presented a great session at the AI Engineer World's Fair Open Models track. As always, don't forget to check the show notes for the YouTube link to their talk, as well as their slides. Watch out and take care.[00:02:35] Luca Intro[00:02:35] Luca Soldaini: Cool. Yeah, thanks for having me over. I'm Luca. I'm a research scientist at the Allen Institute for AI. I threw together a few slides on sort of like a recap of like interesting themes in open models for, for 2024. Have about maybe 20, 25 minutes of slides, and then we can chat if there are any questions.[00:02:57] Luca Soldaini: If I can advance to the next slide. [00:03:00] Okay, cool. So I did the quick check of like, to sort of get a sense of like, how much 2024 was different from 2023. So I went on Hugging Face and sort of get, tried to get a picture of what kind of models were released in 2023 and like, what do we get in 2024?[00:03:16] Luca Soldaini: 2023 we get, we got things like both LLAMA 1 and 2, we got Mistral, we got MPT, Falcon models, I think the YI model came in at the end. Tail end of the year. It was a pretty good year. But then I did the same for 2024. And it's actually quite stark difference. You have models that are, you know, reveling frontier level.[00:03:38] Luca Soldaini: Performance of what you can get from closed models from like Quen, from DeepSeq. We got Llama3. We got all sorts of different models. I added our own Olmo at the bottom. There's this growing group of like, Fully open models that I'm going to touch on a little bit later. But you know, just looking at the slides, it feels like 2024 [00:04:00] was just smooth sailing, happy knees, much better than previous year.[00:04:04] Luca Soldaini: And you know, you can plot you can pick your favorite benchmark Or least favorite, I don't know, depending on what point you're trying to make. And plot, you know, your closed model, your open model and sort of spin it in ways that show that, oh, you know open models are much closer to where closed models are today versus to Versus last year where the gap was fairly significant.[00:04:29] Luca Soldaini: So one thing that I think I don't know if I have to convince people in this room, but usually when I give this talks about like open models, there is always like this background question in, in, in people's mind of like, why should we use open models? APIs argument, you know, it's, it's. Just an HTTP request to get output from a, from one of the best model out there.[00:04:53] Luca Soldaini: Why do I have to set up infra and use local models? And there are really like two answer. There is the more [00:05:00] researchy answer for this, which is where it might be. Background lays, which is just research. If you want to do research on language models, research thrives on, on open models, there is like large swath of research on modeling, on how these models behave on evaluation and inference on mechanistic interpretability that could not happen at all if you didn't have open models they're also for AI builders, they're also like.[00:05:30] Luca Soldaini: Good use cases for using local models. You know, you have some, this is like a very not comprehensive slides, but you have things like there are some application where local models just blow closed models out of the water. So like retrieval, it's a very clear example. We might have like constraints like Edge AI applications where it makes sense.[00:05:51] Luca Soldaini: But even just like in terms of like stability, being able to say this model is not changing under the hood. It's, there's plenty of good cases for, [00:06:00] for open models. And the community is just not models. Is I stole this slide from one of the Quent2 announcement blog posts. But it's super cool to see like how much tech exists around open models and serving them on making them efficient and hosting them.[00:06:18] Luca Soldaini: It's pretty cool. And so. It's if you think about like where the term opens come from, comes from like the open source really open models meet the core tenants of, of open, of open source specifically when it comes around collaboration, there is truly a spirit, like through these open models, you can build on top of other people.[00:06:41] Luca Soldaini: innovation. We see a lot of these even in our own work of like, you know, as we iterate in the various versions of Alma it's not just like every time we collect from scratch all the data. No, the first step is like, okay, what are the cool data sources and datasets people have put [00:07:00] together for language model for training?[00:07:01] Luca Soldaini: Or when it comes to like our post training pipeline We one of the steps is you want to do some DPO and you use a lot of outputs of other models to improve your, your preference model. So it's really having like an open sort of ecosystem benefits and accelerates the development of open models.[00:07:23] The Definition of Open Models[00:07:23] Luca Soldaini: One thing that we got in 2024, which is not a specific model, but I thought it was really significant, is we first got we got our first open source AI definition. So this is from the open source initiative they've been generally the steward of a lot of the open source licenses when it comes to software and so they embarked on this journey in trying to figure out, okay, How does a license, an open source license for a model look like?[00:07:52] Luca Soldaini: Majority of the work is very dry because licenses are dry. So I'm not going to walk through the license step by [00:08:00] step, but I'm just going to pick out one aspect that is very good and then one aspect that personally feels like it needs improvement on the good side. This this open source AI license actually.[00:08:13] Luca Soldaini: This is very intuitive. If you ever build open source software and you have some expectation around like what open source looks like for software for, for AI, sort of matches your intuition. So, the weights need to be fairly available the code must be released with an open source license and there shouldn't be like license clauses that block specific use cases.[00:08:39] Luca Soldaini: So. Under this definition, for example, LLAMA or some of the QUEN models are not open source because the license says you can't use this model for this or it says if you use this model you have to name the output this way or derivative needs to be named that way. Those clauses don't meet open source [00:09:00] definition and so they will not be covered.[00:09:02] Luca Soldaini: The LLAMA license will not be covered under the open source definition. It's not perfect. One of the thing that, um, internally, you know, in discussion with with OSI, we were sort of disappointed is around the language. For data. So you might imagine that an open source AI model means a model where the data is freely available.[00:09:26] Luca Soldaini: There were discussion around that, but at the end of the day, they decided to go with a softened stance where they say a model is open source if you provide sufficient detail information. On how to sort of replicate the data pipeline. So you have an equivalent system, sufficient, sufficiently detailed.[00:09:46] Luca Soldaini: It's very, it's very fuzzy. Don't like that. An equivalent system is also very fuzzy. And this doesn't take into account the accessibility of the process, right? It might be that you provide enough [00:10:00] information, but this process costs, I don't know, 10 million to do. Now the open source definition. Like, any open source license has never been about accessibility, so that's never a factor in open source software, how accessible software is.[00:10:14] Luca Soldaini: I can make a piece of open source, put it on my hard drive, and never access it. That software is still open source, the fact that it's not widely distributed doesn't change the license, but practically there are expectations of like, what we want good open sources to be. So, it's, It's kind of sad to see that the data component in this license is not as, as, Open as some of us would like would like it to be.[00:10:40] Challenges for Open Models[00:10:40] Luca Soldaini: and I linked a blog post that Nathan wrote on the topic that it's less rambly and easier to follow through. One thing that in general, I think it's fair to say about the state of open models in 2024 is that we know a lot more than what we knew in, [00:11:00] in 2023. Like both on the training data, like And the pre training data you curate on like how to do like all the post training, especially like on the RL side.[00:11:10] Luca Soldaini: You know, 2023 was a lot of like throwing random darts at the board. I think 2024, we have clear recipes that, okay, don't get the same results as a closed lab because there is a cost in, in actually matching what they do. But at least we have a good sense of like, okay, this is, this is the path to get state of the art language model.[00:11:31] Luca Soldaini: I think that one thing that it's a downside of 2024 is that I think we are more research constrained in 2023. It feels that, you know, the barrier for compute that you need to, to move innovation along as just being right rising and rising. So like, if you go back to this slide, there is now this, this cluster of models that are sort of released by the.[00:11:57] Luca Soldaini: Compute rich club. Membership is [00:12:00] hotly debated. You know, some people don't want to be. Called the rich because it comes to expectations. Some people want to be called rich, but I don't know, there's debate, but like, these are players that have, you know, 10, 000, 50, 000 GPUs at minimum. And so they can do a lot of work and a lot of exploration and improving models that it's not very accessible.[00:12:21] Luca Soldaini: To give you a sense of like how I personally think about. Research budget for each part of the, of the language model pipeline is like on the pre training side, you can maybe do something with a thousand GPUs, really you want 10, 000. And like, if you want real estate of the art, you know, your deep seek minimum is like 50, 000 and you can scale to infinity.[00:12:44] Luca Soldaini: The more you have, the better it gets. Everyone on that side still complains that they don't have enough GPUs. Post training is a super wide sort of spectrum. You can do as little with like eight GPUs as long as you're able to [00:13:00] run, you know, a good version of, say, a LLAMA model, you can do a lot of work there.[00:13:05] Luca Soldaini: You can scale a lot of the methodology, just like scales with compute, right? If you're interested in you know, your open replication of what OpenAI's O1 is you're going to be on the 10K spectrum of our GPUs. Inference, you can do a lot with very few resources. Evaluation, you can do a lot with, well, I should say at least one GPUs if you want to evaluate GPUs.[00:13:30] Luca Soldaini: Open models but in general, like if you are, if you care a lot about intervention to do on this model, which it's my prefer area of, of research, then, you know, the resources that you need are quite, quite significant. Yeah. One other trends that has emerged in 2024 is this cluster of fully open models.[00:13:54] Luca Soldaini: So Omo the model that we built at ai, two being one of them and you know, it's nice [00:14:00] that it's not just us. There's like a cluster of other mostly research efforts who are working on this. And so it's good to to give you a primer of what like fully open means. So fully open, the easy way to think about it is instead of just releasing a model checkpoint that you run, you release a full recipe so that other people working on it.[00:14:24] Luca Soldaini: Working on that space can pick and choose whatever they want from your recipe and create their own model or improve on top of your model. You're giving out the full pipeline and all the details there instead of just like the end output. So I pull up the screenshot from our recent MOE model.[00:14:43] Luca Soldaini: And like for this model, for example, we released the model itself. Data that was trained on, the code, both for training and inference all the logs that we got through the training run, as well as every intermediate checkpoint and like the fact that you release different part of the pipeline [00:15:00] allows others to do really cool things.[00:15:02] Luca Soldaini: So for example, this tweet from early this year from folks in news research they use our pre training data to do a replication of the BitNet paper in the open. So they took just a Really like the initial part of a pipeline and then the, the thing on top of it. It goes both ways.[00:15:21] Luca Soldaini: So for example, for the Olmo2 model a lot of our pre trained data for the first stage of pre training was from this DCLM initiative that was led by folks Ooh, a variety of ins a variety of institutions. It was a really nice group effort. But you know, for When it was nice to be able to say, okay, you know, the state of the art in terms of like what is done in the open has improved.[00:15:46] AI2 Models - Olmo, Molmo, Pixmo etc[00:15:46] Luca Soldaini: We don't have to like do all this work from scratch to catch up the state of the art. We can just take it directly and integrate it and do our own improvements on top of that. I'm going to spend a few minutes doing like a [00:16:00] shameless plug for some of our fully open recipes. So indulge me in this.[00:16:05] Luca Soldaini: So a few things that we released this year was, as I was mentioning, there's OMOE model which is, I think still is state of the art MOE model in its size class. And it's also. Fully open, so every component of this model is available. We released a multi modal model called Molmo. Molmo is not just a model, but it's a full recipe of how you go from a text only model to a multi modal model, and we apply this recipe on top of Quent checkpoints, on top of Olmo checkpoints, as well as on top of OlmoE.[00:16:37] Luca Soldaini: And I think there'd be a replication doing that on top of Mistral as well. The post training side we recently released 2. 0. 3. Same story. This is a recipe on how you go from a base model to A state of the art post training model. We use the Tulu recipe on top of Olmo, on top of Llama, and then there's been open replication effort [00:17:00] to do that on top of Quen as well.[00:17:02] Luca Soldaini: It's really nice to see like, you know, when your recipe sort of, it's kind of turnkey, you can apply it to different models and it kind of just works. And finally, the last thing we released this year was Olmo 2, which so far is the best state of the art. Fully open language model a Sera combines aspect from all three of these previous models.[00:17:22] Luca Soldaini: What we learn on the data side from MomoE and what we learn on like making models that are easy to adapt from the Momo project and the Tulu project. I will close with a little bit of reflection of like ways this, this ecosystem of open models like it's not all roses. It's not all happy. It feels like day to day, it's always in peril.[00:17:44] Luca Soldaini: And, you know, I talked a little bit about like the compute issues that come with it. But it's really not just compute. One thing that is on top of my mind is due to like the environment and how you know, growing feelings about like how AI is treated. [00:18:00] It's actually harder to get access to a lot of the data that was used to train a lot of the models up to last year.[00:18:06] Luca Soldaini: So this is a screenshot from really fabulous work from Shane Longpre who's, I think is in Europe about Just access of like diminishing access to data for language model pre training. So what they did is they went through every snapshot of common crawl. Common crawl is this publicly available scrape of the, of a subset of the internet.[00:18:29] Luca Soldaini: And they looked at how For any given website whether a website that was accessible in say 2017, what, whether it was accessible or not in 2024. And what they found is as a reaction to like the close like of the existence of closed models like OpenAI or Cloud GPT or Cloud a lot of content owners have blanket Blocked any type of crawling to your website.[00:18:57] Luca Soldaini: And this is something that we see also internally at [00:19:00] AI2. Like one project that we started this year is we wanted to, we wanted to understand, like, if you're a good citizen of the internet and you crawl following sort of norms and policy that have been established in the last 25 years, what can you crawl?[00:19:17] Luca Soldaini: And we found that there's a lot of website where. The norms of how you express preference of whether to crawl your data or not are broken. A lot of people would block a lot of crawling, but do not advertise that in RobustDXT. You can only tell that they're crawling, that they're blocking you in crawling when you try doing it.[00:19:37] Luca Soldaini: Sometimes you can't even crawl the robots. txt to, to check whether you're allowed or not. And then a lot of websites there's, there's like all these technologies that historically have been, have existed to make websites serving easier such as Cloudflare or DNS. They're now being repurposed for blocking AI or any type of crawling [00:20:00] in a way that is Very opaque to the content owners themselves.[00:20:04] Luca Soldaini: So, you know, you go to these websites, you try to access them and they're not available and you get a feeling it's like, Oh, someone changed, something changed on the, on the DNS side that it's blocking this and likely the content owner has no idea. They're just using a Cloudflare for better, you know, load balancing.[00:20:25] Luca Soldaini: And this is something that was sort of sprung on them with very little notice. And I think the problem is this, this blocking or ideas really, it impacts people in different ways. It disproportionately helps companies that have a headstart, which are usually the closed labs and it hurts incoming newcomer players where either have now to do things in a sketchy way or you're never going to get that content that the closed lab might have.[00:20:54] Luca Soldaini: So there's a lot, it was a lot of coverage. I'm going to plug Nathan's blog post again. That is, [00:21:00] that I think the title of this one is very succinct which is like, we're actually not, You know, before thinking about running out of training data, we're actually running out of open training data. And so if we want better open models they should be on top of our mind.[00:21:13] Regulation and Lobbying[00:21:13] Luca Soldaini: The other thing that has emerged is that there is strong lobbying efforts on trying to define any kind of, AI as like a new extremely risky and I want to be precise here. Like the problem is now, um, like the problem is not not considering the risk of this technology. Every technology has risks that, that should always be considered.[00:21:37] Luca Soldaini: The thing that it's like to me is sorry, is ingenious is like just putting this AI on a pedestal and calling it like, An unknown alien technology that has like new and undiscovered potentials to destroy humanity. When in reality, all the dangers I think are rooted in [00:22:00] dangers that we know from existing software industry or existing issues that come with when using software on on a lot of sensitive domains, like medical areas.[00:22:13] Luca Soldaini: And I also noticed a lot of efforts that have actually been going on and trying to make this open model safe. I pasted one here from AI2, but there's actually like a lot of work that has been going on on like, okay, how do you make, if you're distributing this model, Openly, how do you make it safe?[00:22:31] Luca Soldaini: How, what's the right balance between accessibility on open models and safety? And then also there's annoying brushing of sort of concerns that are then proved to be unfounded under the rug. You know, if you remember the beginning of this year, it was all about bio risk of these open models.[00:22:48] Luca Soldaini: The whole thing fizzled because as being Finally, there's been like rigorous research, not just this paper from Cohere folks, but it's been rigorous research showing [00:23:00] that this is really not a concern that we should be worried about. Again, there is a lot of dangerous use of AI applications, but this one was just like, A lobbying ploy to just make things sound scarier than they actually are.[00:23:15] Luca Soldaini: So I got to preface this part. It says, this is my personal opinion. It's not my employer, but I look at things like the SP 1047 from, from California. And I think we kind of dodged a bullet on, on this legislation. We, you know, the open source community, a lot of the community came together at the last, sort of the last minute and did a very good effort trying to explain all the negative impact of this bill.[00:23:43] Luca Soldaini: But There's like, I feel like there's a lot of excitement on building these open models or like researching on these open models. And lobbying is not sexy it's kind of boring but it's sort of necessary to make sure that this ecosystem can, can really [00:24:00] thrive. This end of presentation, I have Some links, emails, sort of standard thing in case anyone wants to reach out and if folks have questions or anything they wanted to discuss.[00:24:13] Luca Soldaini: Is there an open floor? I think we have Sophia[00:24:16] swyx: who wants to who one, one very important open model that we haven't covered is Mistral. Ask her on this slide. Yeah, yeah. Well, well, it's nice to have the Mistral person talk recap the year in Mistral. But while Sophia gets set up, does anyone have like, just thoughts or questions about the progress in this space?[00:24:32] Questions - Incentive Alignment[00:24:32] swyx: Do you always have questions?[00:24:34] Quesiton: I'm very curious how we should build incentives to build open models, things like Francois Chollet's ArcPrize, and other initiatives like that. What is your opinion on how we should better align incentives in the community so that open models stay open?[00:24:49] Luca Soldaini: The incentive bit is, like, really hard.[00:24:51] Luca Soldaini: Like, even It's something that I actually, even we think a lot about it internally because like building open models is risky. [00:25:00] It's very expensive. And so people don't want to take risky bets. I think the, definitely like the challenges like our challenge, I think those are like very valid approaches for it.[00:25:13] Luca Soldaini: And then I think in general, promoting, building, so, any kind of effort to participate in this challenge, in those challenges, if we can promote doing that on top of open models and sort of really lean into like this multiplier effect, I think that is a good way to go. If there were more money for that.[00:25:35] Luca Soldaini: For efforts like research efforts around open models. There's a lot of, I think there's a lot of investments in companies that at the moment are releasing their model in the open, which is really cool. But it's usually more because of commercial interest and not wanting to support this, this like open models in the longterm, it's a really hard problem because I think everyone is operating sort of [00:26:00] in what.[00:26:01] Luca Soldaini: Everyone is at their local maximum, right? In ways that really optimize their position on the market. Global maximum is harder to achieve.[00:26:11] Question2: Can I ask one question? No.[00:26:12] Luca Soldaini: Yeah.[00:26:13] Question2: So I think one of the gap between the closed and open source models is the mutability. So the closed source models like chat GPT works pretty good on the low resource languages, which is not the same on the open, open source models, right?[00:26:27] Question2: So is it in your plan to improve on that?[00:26:32] Luca Soldaini: I think in general,[00:26:32] Luca Soldaini: yes, is I think it's. I think we'll see a lot of improvements there in, like, 2025. Like, there's groups like, Procurement English on the smaller side that are already working on, like, better crawl support, multilingual support. I think what I'm trying to say here is you really want to be experts.[00:26:54] Luca Soldaini: who are actually in those countries that teach those languages to [00:27:00] participate in the international community. To give you, like, a very easy example I'm originally from Italy. I think I'm terribly equipped to build a model that works well in Italian. Because one of the things you need to be able to do is having that knowledge of, like, okay, how do I access, you know, how Libraries, or content that is from this region that covers this language.[00:27:23] Luca Soldaini: I've been in the US long enough that I no longer know. So, I think that's the efforts that folks in Central Europe, for example, are doing. Around like, okay, let's tap into regional communities. To get access you know, to bring in collaborators from those areas. I think it's going to be, like, very crucial for getting products there.[00:27:46] Mistral intro[00:27:46] Sophia Yang: Hi everyone. Yeah, I'm super excited to be here to talk to you guys about Mistral. A really short and quick recap of what we have done, what kind of models and products we have released in the [00:28:00] past year and a half. So most of you We have already known that we are a small startup funded about a year and a half ago in Paris in May, 2003, it was funded by three of our co founders, and in September, 2003, we released our first open source model, Mistral 7b yeah, how, how many of you have used or heard about Mistral 7b?[00:28:24] Sophia Yang: Hey, pretty much everyone. Thank you. Yeah, it's our Pretty popular and community. Our committee really loved this model, and in December 23, we, we released another popular model with the MLE architecture Mr. A X seven B and oh. Going into this year, you can see we have released a lot of things this year.[00:28:46] Sophia Yang: First of all, in February 2004, we released MrSmall, MrLarge, LeChat, which is our chat interface, I will show you in a little bit. We released an embedding model for, you [00:29:00] know, converting your text into embedding vectors, and all of our models are available. The, the big cloud resources. So you can use our model on Google cloud, AWS, Azure Snowflake, IBM.[00:29:16] Sophia Yang: So very useful for enterprise who wants to use our model through cloud. And in April and May this year, we released another powerful open source MOE model, AX22B. And we also released our first code. Code Model Coastal, which is amazing at 80 plus languages. And then we provided another fine tuning service for customization.[00:29:41] Sophia Yang: So because we know the community love to fine tune our models, so we provide you a very nice and easy option for you to fine tune our model on our platform. And also we released our fine tuning code base called Menstrual finetune. It's open source, so feel free to take it. Take a look and.[00:29:58] Sophia Yang: More models. [00:30:00] On July 2, November this year, we released many, many other models. First of all is the two new small, best small models. We have Minestra 3B great for Deploying on edge devices we have Minstrel 8B if you used to use Minstrel 7B, Minstrel 8B is a great replacement with much stronger performance than Minstrel 7B.[00:30:25] Sophia Yang: We also collaborated with NVIDIA and open sourced another model, Nemo 12B another great model. And Just a few weeks ago, we updated Mistral Large with the version 2 with the updated, updated state of the art features and really great function calling capabilities. It's supporting function calling in LatentNate.[00:30:45] Sophia Yang: And we released two multimodal models Pixtral 12b. It's this open source and Pixtral Large just amazing model for, models for not understanding images, but also great at text understanding. So. Yeah, a [00:31:00] lot of the image models are not so good at textual understanding, but pixel large and pixel 12b are good at both image understanding and textual understanding.[00:31:09] Sophia Yang: And of course, we have models for research. Coastal Mamba is built on Mamba architecture and MathRoll, great with working with math problems. So yeah, that's another model.[00:31:29] Sophia Yang: Here's another view of our model reference. We have several premier models, which means these models are mostly available through our API. I mean, all of the models are available throughout our API, except for Ministry 3B. But for the premier model, they have a special license. Minstrel research license, you can use it for free for exploration, but if you want to use it for enterprise for production use, you will need to purchase a license [00:32:00] from us.[00:32:00] Sophia Yang: So on the top row here, we have Minstrel 3b and 8b as our premier model. Minstrel small for best, best low latency use cases, MrLarge is great for your most sophisticated use cases. PixelLarge is the frontier class multimodal model. And, and we have Coastral for great for coding and then again, MrEmbedding model.[00:32:22] Sophia Yang: And The bottom, the bottom of the slides here, we have several Apache 2. 0 licensed open way models. Free for the community to use, and also if you want to fine tune it, use it for customization, production, feel free to do so. The latest, we have Pixtros 3 12b. We also have Mr. Nemo mum, Coastal Mamba and Mastro, as I mentioned, and we have three legacy models that we don't update anymore.[00:32:49] Sophia Yang: So we recommend you to move to our newer models if you are still using them. And then, just a few weeks ago, [00:33:00] we did a lot of, uh, improvements to our code interface, Lachette. How many of you have used Lachette? Oh, no. Only a few. Okay. I highly recommend Lachette. It's chat. mistral. ai. It's free to use.[00:33:16] Sophia Yang: It has all the amazing capabilities I'm going to show you right now. But before that, Lachette in French means cat. So this is actually a cat logo. If you You can tell this is the cat eyes. Yeah. So first of all, I want to show you something Maybe let's, let's take a look at image understanding.[00:33:36] Sophia Yang: So here I have a receipts and I want to ask, just going to get the prompts. Cool. So basically I have a receipt and I said I ordered I don't know. Coffee and the sausage. How much do I owe? Add a 18 percent tip. So hopefully it was able to get the cost of the coffee and the [00:34:00] sausage and ignore the other things.[00:34:03] Sophia Yang: And yeah, I don't really understand this, but I think this is coffee. It's yeah. Nine, eight. And then cost of the sausage, we have 22 here. And then it was able to add the cost, calculate the tip, and all that. Great. So, it's great at image understanding, it's great at OCR tasks. So, if you have OCR tasks, please use it.[00:34:28] Sophia Yang: It's free on the chat. It's also available through our API. And also I want to show you a Canvas example. A lot of you may have used Canvas with other tools before. But, With Lachat, it's completely free again. Here, I'm asking it to create a canvas that's used PyScript to execute Python in my browser.[00:34:51] Sophia Yang: Let's see if it works. Import this. Okay, so, yeah, so basically it's executing [00:35:00] Python here. Exactly what we wanted. And the other day, I was trying to ask Lachat to create a game for me. Let's see if we can make it work. Yeah, the Tetris game. Yep. Let's just get one row. Maybe. Oh no. Okay. All right. You get the idea. I failed my mission. Okay. Here we go. Yay! Cool. Yeah. So as you can see, Lachet can write, like, a code about a simple game pretty easily. And you can ask Lachet to explain the code. Make updates however you like. Another example. There is a bar here I want to move.[00:35:48] Sophia Yang: Okay, great, okay. And let's go back to another one. Yeah, we also have web search capabilities. Like, you can [00:36:00] ask what's the latest AI news. Image generation is pretty cool. Generate an image about researchers. Okay. In Vancouver? Yeah, it's Black Forest Labs flux Pro. Again, this is free, so Oh, cool.[00:36:19] Sophia Yang: I guess researchers here are mostly from University of British Columbia. That's smart. Yeah. So this is Laia ira. Please feel free to use it. And let me know if you have any feedback. We're always looking for improvement and we're gonna release a lot more powerful features in the coming years.[00:36:37] Sophia Yang: Thank you. Get full access to Latent Space at www.latent.space/subscribe

Sophia Yang, Head of Developer Relations at Mistral AI, discusses why they don't open source everything, and how they strike a balance between openness and growing their business. She also discusses how Mistral AI approaches developer relations and community building to advance AI. Key Takeaways:  The goal and vision of Mistral AI Why Mistral AI doesn't open source all their models How Brave and Mistral AI are currently integrated, enhancing Brave's Leo AI tools and search engine Ways MistralAI is investing in community through large-scale hackathons Why specialized models are the future of innovation in AI Guest Bio:  Sophia Yang is the Head of Developer Relations at Mistral AI, where she leads developer education, developer ecosystem partnerships, and community engagement. She is passionate about the AI and open-source communities, and she is committed to empowering their growth and learning. She holds an M.S. in Computer Science, an M.S. in Statistics, and a Ph.D. in Educational Psychology from The University of Texas at Austin. ---------------------------------------------------------------------------------------- About this Show: The Brave Technologist is here to shed light on the opportunities and challenges of emerging tech. To make it digestible, less scary, and more approachable for all! Join us as we embark on a mission to demystify artificial intelligence, challenge the status quo, and empower everyday people to embrace the digital revolution. Whether you're a tech enthusiast, a curious mind, or an industry professional, this podcast invites you to join the conversation and explore the future of AI together. The Brave Technologist Podcast is hosted by Luke Mulks, VP Business Operations at Brave Software—makers of the privacy-respecting Brave browser and Search engine, and now powering AI everywhere with the Brave Search API. Music by: Ari Dvorin Produced by: Sam Laliberte  

We introduce Mixtral 8x7B, a Sparse Mixture of Experts (SMoE) language model. Mixtral has the same architecture as Mistral 7B, with the difference that each layer is composed of 8 feedforward blocks (i.e. experts). For every token, at each layer, a router network selects two experts to process the current state and combine their outputs. Even though each token only sees two experts, the selected experts can be different at each timestep. As a result, each token has access to 47B parameters, but only uses 13B active parameters during inference. Mixtral was trained with a context size of 32k tokens and it outperforms or matches Llama 2 70B and GPT-3.5 across all evaluated benchmarks. In particular, Mixtral vastly outperforms Llama 2 70B on mathematics, code generation, and multilingual benchmarks. We also provide a model fine-tuned to follow instructions, Mixtral 8x7B - Instruct, that surpasses GPT-3.5 Turbo, Claude-2.1, Gemini Pro, and Llama 2 70B - chat model on human benchmarks. Both the base and instruct models are released under the Apache 2.0 license. 2024: Albert Q. Jiang, Alexandre Sablayrolles, Antoine Roux, Arthur Mensch, Blanche Savary, Chris Bamford, Devendra Singh Chaplot, Diego de Las Casas, Emma Bou Hanna, Florian Bressand, Gianna Lengyel, Guillaume Bour, Guillaume Lample, L'elio Renard Lavaud, Lucile Saulnier, Marie-Anne Lachaux, Pierre Stock, Sandeep Subramanian, Sophia Yang, Szymon Antoniak, Teven Le Scao, Théophile Gervet, Thibaut Lavril, Thomas Wang, Timothée Lacroix, William El Sayed https://arxiv.org/pdf/2401.04088.pdf

Sean and Kelly speak with Anaconda and their outreach program. Anaconda supports educators and learners with the ability to understand and interpret data. This leads to better decision-making and a world where people are empowered to create positive change. Episode Errata: * The hackday event referenced in the episode was related to Pyscript and more information will come out on that shortly. * The data science competition for high school students referenced in the episode is called Data Science Expo and will be piloted in the 2022-2023 school year. Note: we had to go to the cloud-based recording backup for this episode, so you may notice a few issues with audio quality. Our editor did his best to clean it up, but there are a few rough spots. Special Guests: Albert Defusco and Sophia Yang.

Jenna interviews Sophia Yang, the Founder of Threading Change, about sustainability and intersectionality in the fashion industry. The conversation focuses on Threading Change's key pillars: transparency, authenticity, and vulnerability. Learn about the toxicity of fast fashion, avenues for change, and how Sophia is threading change in the industry to empower marginalized voices. Episode references and resources Threading Change website Membership network Fashion Revolution United Nations Fashion Industry Charter Guardian article: H&M emissions CTA sustainable fashion blog post CTA episode 16: fast fashion and community action with Yoshi Matsuzaki Make sure to rate, subscribe and follow the Clear the Air Podcast, and follow the journey on social media: Website: https://ctablog.ca Podcast site: https://ctablog.ca/podcast Instagram: @_ctablog Twitter: @_ctablog ABOUT THE PODCAST Clear the Air seeks to educate, empower and mobilize youth to take action against climate change. These weekly episodes will focus on a specific theme, teaching you how to take action RIGHT NOW in your own life. By listening to the podcast, you will become a sustainability expert in no time. Jenna Phillips is the podcast host, a passionate university student, and a local climate action leader. She uses her expertise and desire for change to make a difference in the lives of others. It's time to Clear the Air of all this confusion about climate change. It's time to learn how we, the youth climate leaders of today, can make a change. It's time to take our future into our own hands.

Watch the live stream: Watch on YouTube About the show Sponsored by Mergify! Special guest: Pat Decker Michael #0: New live stream / recording time: 12pm US PT on Tuesdays. Please subscribe to our YouTube channel to get notified and be part of the episodes. Brian #1: BTW, don't make a public repo private How we lost 54k GitHub stars Jakub Roztočil HTTPie kinda sorta accidentally flipped their main repo to private for a sec. And dropped the star count from 54k to 0 oops They're back up to 16k, as of today. But ouch. “HTTPie is a command-line HTTP client. Its goal is to make CLI interaction with web services as human-friendly as possible. HTTPie is designed for testing, debugging, and generally interacting with APIs & HTTP servers. The http & https commands allow for creating and sending arbitrary HTTP requests. They use simple and natural syntax and provide formatted and colorized output.” Actually, pretty cool tool to use for developing and testing APIs. Michael #2: The counter-intuitive rise of Python in scientific computing via Galen Swint In our laboratory, a polarizing debate rages since around 2010, summarized by this question: Why are more and more time-critical scientific computations formerly performed in Fortran now written in Python, a slower language? Python has the reputation of being slow, i.e. significantly slower than compiled languages such as Fortran, C or Rust. So yes, plain Python is much slower than Fortran. However, this comparison makes little sense, as scientific uses of Python do not rely on plain Python. Used the right way, Python is slightly slower than compiled code. Pat #3: Meta donates $300,000 to PSF to add a second year for the Developer in Residence Brian #4: Dashboards in Python Two suggestions from Marc Skov Madsen The Easiest Way to Create an Interactive Dashboard in Python Sophia Yang & Mark Skov Madsen Includes animated gif showing the dashboard video of Sophia walking through the article in under 6 minutes “Turn Pandas pipelines into a dashboard using hvPlot .interactive" hvPlot is part of HoloViz and this example is pretty short and amazing to get a great dashboard with controls up very quickly. Python Dashboarding Shootout and Showdown | PyData Global 2021 5 speakers, 4 dashboard libraries, nice for comparison. Nice clickable index posted by Duy Nguyen 00:00 - Begin and Welcome 03:15 - Intro to the 4 Dashboarding libraries 07:04 - Plotly - Nicolas Kruchten 22:01 - Panel - Marc Skov Madsen 37:38 - voila - Sylvain Corlay 51:36 - Streamlit - Adrien Treuille 01:10:52 - Discussion Topics Michael #5: sourcepy by Dave Chevell Sourcepy lets you source python scripts natively inside your shell Imagine a Python script with functions in it. This converts those to CLI commands (kind of like entrypoints, but simpler) Type hints can be used to coerce input values into their corresponding types. standard IO type hints can be used to target stdin at different arguments and to receive the sys.stdin Sourcepy has full support for asyncio syntax Pat #6: Xonsh Xonsh Shell Combines the Best of Bash Shell and Python in Linux Terminal Awesome demo video (50 min) https://youtu.be/x85LSyCxiw8 Extras Pat: Donate to the PSF by using https://rewards.microsoft.com Joke: Can you really quit vim? Joke: Forgetting how to count

How do we remake fashion so that it is regenerative, fossil-free, inclusive, and equitable? Fashion and textiles are where climate change, waste, labour rights, and social justice all come together. Every single one of us interacts with clothing in our everyday lives, and fashion is currently one of Earth's most polluting industries. We have an opportunity to remake our fashion system, so that it becomes the fertile ground for thriving local economies, creative expression, and circular loops that keep us in balance within nature's boundaries.  Sophia Yang, Founder and Executive Director of Threading Change, joins Reseed host Alice Irene Whittaker for a conversation about fashion, justice, gender, circular economy, and climate - and how they all weave together. Read the transcript and show notes at reseed.ca. 

In this part two of our conversation with Sophia Yang (check out episode 8 for part one!), we discuss how we can create a more equitable and intersectional fashion ecosystem.Sophia, who is the Founder & Executive Director of ethical fashion organization Threading Change, is sharing: How we can get started with or continue fashion activism,What artivism is and how it could bring more people into the sustainable fashion and social justice movements,The importance of engaging youth in ethical fashion,and more.  FULL SHOW NOTES & TRANSCRIPThttps://www.consciouslifeandstyle.com/intersectional-sustainable-fashion-future/  QUICK LINKS:Fashion Revolution: Take ActionRemakeTextile Talks: Threading Change's Webinar SeriesThreading Change's Current CampaignsClothes Busters Webinar SeriesContact Threading Change  CONNECT WITH SOPHIA:WebsiteInstagramTwitterSoundcloud  CONNECT WITH THREADING CHANGE:WebsiteInstagram  CONNECT WITH CONSCIOUS STYLE:Conscious Life & Style WebsiteInstagramPinterestConscious Edit Newsletter  

In this powerful and illuminating two-part conversation, Sophia Yang of Threading Change discusses how colonialism has not only shaped fashion, but how colonial systems are deeply embedded in the industry today.Sophia also shares what equity really is and how we must address exploitation in fashion at its core; the realities of racism and colonialism in not just fast fashion, but the conscious fashion space as well; and why we need to decentralize and decolonize the Eurocentric understanding of land and labor in the fashion space.  FULL SHOW NOTES & TRANSCRIPT:consciouslifeandstyle.com/fashion-colonial-roots-and-realities  QUICK LINKS:The OR FoundationKantamanto Market in GhanaZara deletes statement against forced labor from website Background on China and forced Uighur laborThe brands implicated in report on forced labor in China  CONNECT WITH SOPHIA:WebsiteInstagramTwitterSoundcloud  CONNECT WITH THREADING CHANGE:WebsiteInstagram  CONNECT WITH CONSCIOUS STYLE:Conscious Life & Style WebsiteInstagramPinterestConscious Edit Newsletter  

Sophia Yang speaks with Wolfgang about Threading Change, “a youth-led not-for-profit organization envisioning a future where fashion is ethical and circular, rooted in justice with climate, gender, and racial equity at the forefront.” In this motivating conversation Sophia discusses relationships between fashion, racism, environmental destruction, and what can be done to change these current realities. This conversation is part of our ongoing partnership with Taking it Global For more information on the programs we provide visit: http://risingyouth.ca See here for more information about Threading Change GET INVOLVED WITH THREADING CHANGE: 1. Join #ClothesBusters month: Threading Change's Spring Cleaning educational campaign here to demystify and bust popular clothing myths! 2. Threading Change is hiring! (unpaid for now, paid to start in summer) 3. Sign up for Threading Change's newsletter to get resources and stay up to date with local campaigns OTHER WAYS TO GET INVOLVED: 1. Join the global Fashion Revolution Week and ask: #WHOMADEMYCLOTHES? (Fashion Revolution's website also has tons of other great reading, organizing, and campaigning resources as well!) 2. Join the #PayUp movement 3. Check out Slow Factory Foundation's AMAZING Fashion Education courses for BIPOC 4. Sign the petition to end Uyghur forced labour in China READINGS/RESOURCES: 1. Blog post Sophia wrote on why we need to start Threading Change 2. Threading Change's global launch webinar 3. How to Buy Clothes Built to Last by Kendra Pierre-Louis 4. Vox article: Why is it so hard for clothing manufacturers to pay a living wage? 5. Gone Thrifting: How to Build A Better Thrifting System by Emily Stochl 6. What A Waste 2.0: A Global Snapshot of Solid Waste Management to 2050 7. Global Fashion Agenda's Fashion on Climate report PODCASTS/FILMS: 1. Film: Unravel 2. The True Cost (all on Youtube for free!) 3. Conscious Chatter 4. Wardrobe Crisis 5. Fashion is a great teacher

本期是北欧系列的“加餐”篇，在前两期节目里，我们先对北欧有了一个预览，然后以又详细聊了聊丹麦的社会和风土人情。这两期节目很受欢迎，大家留言也很多。而北欧系列的分享人，来自壮游者二群的听友Sophia，还有很多很珍贵的北欧旅行私人记忆，就以加更的形式推出，以报答各位听友的热情。在这期节目里呢，Sophia将讲述她在瑞典和冰岛两地追逐极光的经历，包括蒸混浴桑拿、驾驶狗拉雪橇等；还会讲述在挪威攀爬著名的步道岩的经历，她还带着姜醋到了挪威的卑尔根...在冰岛，徜徉于冬夏不同的景色，还品尝了10万年前的味道。你准备好了么，我们出发了。|故事节点|08:20 看极光的必要条件和我失败了...13:44 驾驶狗拉雪橇是一种什么体验？15:44 混浴桑拿，反正什么也看不见...18:58 诺贝尔颁奖大厅蓝色大厅咋没蓝色呢？20:48 一艘倒霉的沉船成了一个博物馆24:34 布道岩顶，我当时咋不害怕呢？28:52 挪威峡湾里的海鸥会特技？30:52 我带着姜醋汁去挪威吃螃蟹34:03 冰岛一定要来两次，夏天一次，冬天一次37:00 看得见风景的音乐厅和JJ博物馆39:18 踏破棉鞋无觅处，我看到极光了！45:27 抗议007和我尝到了10万年前的味道47:52 7年后，老奶奶走了，那家旅馆也走了|壮游者|Sophia：旅行是生活的解药。走遍五大洲，最爱还是欧洲，括弧：挥霍了五年青春岁月的北欧。等待探索的目的地清单越来越长，期待下一次旅行。|主播|Yang：听到600米布道岩被吓得腿软的男子。壮游者是一档独立播客，很需要您的支持。您可以通过微信公众号“壮游者”文章(本期相关图片也在文章里呈现)下方的“喜欢作者”进行赞助，也可以通过知福宝zhuangyouzhe@126.com进行赞助。也可微信添加"zhuangyouzhe2018"拉你进“壮游者”听众群与主播和听友直接交流。最后，如果您喜欢本期的节目，请您顺手转发给身边的朋友。这样，会让更多的人知道壮游者的存在。谢谢你，让我们有机会一起前行。

今天我们的壮游者是曾在瑞典和丹麦一共生活了5年的Sophia，我们的目的地是北欧——注意，北欧是一个大的地理概念。这是壮游者的一个尝试，把视角放到更大的一个区域里，这样会让话题有更多的交叉比对的可能性。关于北欧是一个系列节目，今天是第一部分，我们将了解到北欧五国相爱相杀的历史、北欧神话对西方和英语世界的影响、圣诞老人归属之争、北欧的高福利政策、不鼓励个人英雄主义打击出头鸟的詹特法则、北欧人的社交恐惧和抑郁的冬天......通过本期节目，您一定会对北欧有一个新的认识。下集预告：字幕组成员Sophia将通过一部丹麦剧集《Borgen》(权力的堡垒)来聊一聊丹麦的社会现实，比如女性地位、新闻自由的边缘、格陵兰岛的自治问题、左右派的理念冲突，包括你所不知道的丹麦猪肉问题。在那生活了三年，Sophia也会给大家分享哥本哈根这个城市的魅力。下期依然，不容错过。|故事节点|00:03 夸你一下：《世界新闻》和文字的力量03:35 北欧音乐kulning：对牲畜和大自然的召唤07:42 北欧五国和他们的相爱相杀16:33 圣诞老人到底是芬兰人还是瑞典人？20:47 北欧神话：星期四要迎雷神？24:04 老实交代，北欧哪儿的男子最帅？26:09 五个国家居然有三个语系？32:43 最早的国旗和统一的设计元素35:57 高收入社会的低调和最贵的挪威46:19 居然有度假金？丹麦社会福利到底有多高！55:01 政府鼓励：度假要为爱啪啪啪！68:25 丹麦的詹特法则：别做出头鸟 72:56 社交恐惧和高中即发完的好友券80:17 极夜的抑郁和快乐药片|壮游者|Sophia：旅行是生活的解药。走遍五大洲，最爱还是欧洲，括弧：挥霍了五年青春岁月的北欧。等待探索的目的地清单越来越长，期待下一次旅行。|主播|Yang：惊讶于北欧高福利的一名男子。壮游者是一档独立播客，很需要您的支持。您可以通过微信公众号“壮游者”文章(本期相关图片也在文章里呈现)下方的“喜欢作者”进行赞助，也可以通过知福宝zhuangyouzhe@126.com进行赞助。也可微信添加"zhuangyouzhe2018"拉你进“壮游者”听众群与主播和听友直接交流。最后，如果您喜欢本期的节目，请您顺手转发给身边的朋友。这样，会让更多的人知道壮游者的存在。谢谢你，让我们有机会一起前行。

今天我们的壮游者是曾在瑞典和丹麦一共生活了5年的Sophia，我们的目的地是北欧——注意，北欧是一个大的地理概念。这是壮游者的一个尝试，把视角放到更大的一个区域里，这样会让话题有更多的交叉比对的可能性。关于北欧是一个系列节目，今天是第一部分，我们将了解到北欧五国相爱相杀的历史、北欧神话对西方和英语世界的影响、圣诞老人归属之争、北欧的高福利政策、不鼓励个人英雄主义打击出头鸟的詹特法则、北欧人的社交恐惧和抑郁的冬天......通过本期节目，您一定会对北欧有一个新的认识。下集预告：字幕组成员Sophia将通过一部丹麦剧集《Borgen》(权力的堡垒)来聊一聊丹麦的社会现实，比如女性地位、新闻自由的边缘、格陵兰岛的自治问题、左右派的理念冲突，包括你所不知道的丹麦猪肉问题。在那生活了三年，Sophia也会给大家分享哥本哈根这个城市的魅力。下期依然，不容错过。|故事节点|00:03 夸你一下：《世界新闻》和文字的力量03:35 北欧音乐kulning：对牲畜和大自然的召唤07:42 北欧五国和他们的相爱相杀16:33 圣诞老人到底是芬兰人还是瑞典人？20:47 北欧神话：星期四要迎雷神？24:04 老实交代，北欧哪儿的男子最帅？26:09 五个国家居然有三个语系？32:43 最早的国旗和统一的设计元素35:57 高收入社会的低调和最贵的挪威46:19 居然有度假金？丹麦社会福利到底有多高！55:01 政府鼓励：度假要为爱啪啪啪！68:25 丹麦的詹特法则：别做出头鸟 72:56 社交恐惧和高中即发完的好友券80:17 极夜的抑郁和快乐药片|壮游者|Sophia：旅行是生活的解药。走遍五大洲，最爱还是欧洲，括弧：挥霍了五年青春岁月的北欧。等待探索的目的地清单越来越长，期待下一次旅行。|主播|Yang：惊讶于北欧高福利的一名男子。壮游者是一档独立播客，很需要您的支持。您可以通过微信公众号“壮游者”文章(本期相关图片也在文章里呈现)下方的“喜欢作者”进行赞助，也可以通过知福宝zhuangyouzhe@126.com进行赞助。也可微信添加"zhuangyouzhe2018"拉你进“壮游者”听众群与主播和听友直接交流。最后，如果您喜欢本期的节目，请您顺手转发给身边的朋友。这样，会让更多的人知道壮游者的存在。谢谢你，让我们有机会一起前行。

The University of Alberta has confirmed that remote work continues through Winter 2021 Semester, there will be no change to the current work remote directive until April 30th, 2021. Produced by Sophia Yang.

AHS asks: If you test positive, tell your close contacts. The University of Alberta has a new webpage to share the number of on-campus community members who have reported a positive COVID-19 test during the last three weeks by campus. https://www.ualberta.ca/covid-19/campus-safety/tracking-covid-19-on-our-campuses.html Produced by Sophia Yang.

Today's update is on COVID-19-like symptoms from your flu shot: Some people may have temporary side effects after getting flu shots. Alberta Health Services states that those who have side effects that are the same as COVID-19 symptoms must stay home and isolate, and could return to normal activities only if their side effects go away within 48 hours. Produced by Sophia Yang.

An update on the new health measures in Edmonton Zone: Mandatory measures of a 15-person limit on social and family gatherings, and voluntary measures on limiting cohorts to no more than 3. Produced by Sophia Yang.

Update for the U of A community this week: St. Joseph's College residents fully recovered & isolation complete; Virtual fall convocation on November 20. Produced by Sophia Yang.

No new cases in St. Joseph's College Residence outbreak; U of A varsity athletic in-person training gradually start to recommence; A combination of in-person, remote, and online instruction in Winter 2021. Produced by Sophia Yang.

There has been an outbreak of COVID-19 in St. Joseph's College Men's Residence at the University of Alberta's North Campus. Five students tested positive; All infected individuals covering in self-isolation. Since the cases also touched the U of A athletic community, the university has temporarily suspended all in-person varsity athletic activities for 14 days. Produced by Sophia Yang.

Masks are now available in select vending machines on the University of Alberta's North Campus, including HUB, CAB, DICE, VVC, ECHA, and Peter Lougheed Hall; The North Campus Bookstore is now open for in-person and or online purchases. Produced by Sophia Yang.

The University of Alberta Health Centre Pharmacy is offering asymptomatic testing. Any person who wants to be tested for COVID-19 can now be tested, even if they don't have symptoms. A list of pharmacies in Alberta that offer asymptomatic testing: https://www.ab.bluecross.ca/news/asymptomatic-testing.php Produced by Sophia Yang.

As you may already know, we specialize in telling food stories in Edmonton, Alberta, and we've produced a whole series of podcast episodes in the first season. But in this season, That's Food producer Sophia Yang tried something different, and technically a tricky way of storytelling. As someone who works in the food industry in this extraordinary time, Sophia is a hundred percent sure things have changed in our food scene. In this episode, Sophia goes on the streets and interview random Edmontonians who have something to do with food and check on how they're doing. (Oh, and don't worry, she's been wearing a mask and kept perfect social distancing the whole time.)

An update on University of Alberta library spaces. The only library space open for students, staff, and faculty is the Cameron Library (main floor and basement). Reservation only; No food or drink allowed; Masks and social distancing are mandatory. Produced by Sophia Yang.

There are a couple options for student transit access now available as a result of the Edmonton City Council meeting on August 19th, including the updated "Ride Transit Program" that is based on an individual's personal income. The Student Union states that they will continue working towards more equitable student transit options. Further notice will be updated on the student union website and social media pages. Produced by Sophia Yang.

Update on the Returning to Campus eCourse: The University of Alberta now provides a 10-minute online program that will help understand how to safely return to campus during COVID-19, available to all employees and students. Produced by Sophia Yang.

For those who are planning or expecting events for this fall, keep in mind that the University of Alberta will follow all Government of Alberta health directives on events and gatherings; Since the university is limiting in-person events to those intended for U of A faculty, staff, and students, no public events will be held for now. Produced by Sophia Yang.

This week's update for the U of A community is on the quarantine and isolation information for Fall 2020 international students. Produced by Sophia Yang.

Updates: Wear masks on all U of A campuses; COVID-19 advisories bulletins updated for students, faculties, and staff. Produced by Sophia Yang.

This week's campus update is on face masks on U of A campuses and in Edmonton, and U of A's isolation accommodation program. (To be short: Wear your face masks and stay away from each other!) Produced by Sophia Yang.

Federal government announces support for international students studying at Canadian universities (on the eligibility of study permits and post-graduate work permits); University of Alberta student services remain available remotely. Produced by Sophia Yang.

This week, the University of Alberta updated the course information for Fall 2020. Students can now check their remote delivered and or in-person courses information on the U of A Office of Registrar webpage or on Bear Tracks. Produced by Sophia Yang.

News update for the U of A community: Information for instructors and students about Fall 2020 and the upcoming 2020-21 academic year can now be found on the new Campus Life website; Campus and community recreation facilities are reopening. Produced by Sophia Yang.

On this episode, correspondents Chris Chang-Yen Phillips and Sophia Yang do lunch with Keren Tang and Sarah Chan to discuss how Chinese communities in Edmonton continue to grow strong. Hungry? Here are the restaurants featured on this episode: BaoBao, Silk Road, Padmanadi, Saiwoo Garden and Happy Noodles (no website, but you can find them at 4204 115 street;  780-709-2686). Links: Visit Edmonton Chinese Bilingual Education Association. Learn more about the Chinese Cultural Legacy Fund. Check out United Way Alberta Capital Region. Follow Keren Tang and Sarah Chan on Twitter. Hear more from Chris Chang-Yen Phillips and Sophia Yang. See the COVID-19 […]

University of Alberta Campus and Community Recreation is offering a variety of fitness and recreation programs this summer; The U of A Libraries provide curbside pickup service for students, faculty, and staff. Produced by Sophia Yang.

Updates for the U of A community: curbside pickup service of the U of A libraries; spring/summer U-Pass program suspended. Produced by Sophia Yang.

News update for the University of Alberta community. Although Alberta is lifting some restrictions as of June 12th, the U of A will move into their own Phase 2, hopefully in July. ETS starts to resume fare collection on June 15th while Winter 2020 U-Passes will still be accepted until the end of June. Produced by Sophia Yang.

If you have listened to our first quarantine special, you already know our producers are trying easy food to make at home. Since we've been living in this New Normal for over two months now, oatmeal every day starts to be too much. Without further ado, let us help you discover new recipes (that can actually be processed)! In this episode, That's Food producer Melania Antoszko, Katelin Karbonik, Sophia Yang, and Ralph Garcia shared the food and recipes they discovered during the quarantine. Jump into our new special episode with a snack fact about everyone's quarantine pet —— sourdough.

Updates for the U of A community: Edmonton's State of Local Emergency has lifted; Students and employees continue to work remotely; Updated FAQs section for resuming on-campus research. Produced by Sophia Yang.

Updates for University of Alberta students, produced by Sophia Yang. The Government of Alberta has shared a relaunch guide for post-secondary institutions (link below). The UofA community expect various public health restrictions while the Premier noted plans to lift the State of Emergency in Alberta. https://www.alberta.ca/assets/documents/covid-19-relaunch-guidance-post-secondary-institutions.pdf

Things are different in our lives now. In terms of food, we're also adjusting to new home cooking styles. That's why we decide to drop two quarantine-special episodes for our listeners before diving into our regular season 2 episodes. In this episode, That's Food producers Ralph Garcia, Melania Antoszko, and Katelin Karbonik introduce some of their easy food to make during this special time. May the sound of food gives you that therapy you always want. (Snack fact by Sophia Yang.)

Updates on the University of Alberta's virtual Spring convocation and 2020/21 residence services. Produced by Sophia Yang.

Updates on the announcement on fall term 2020 at the University of Alberta, and the University Health Centre. Produced by Sophia Yang.

An update on UAlberta's ONEcard and parking services, laptop lending program for students, and the Spring convocation. Produced by Sophia Yang.

An update on requesting term feedback and letters of reference, and new COVID-19 research funding opportunities email notifications. Produced by Sophia Yang.

Glass Bookshop and Audreys Books, the newest and the oldest indie bookstores in Edmonton, are adopting new operating strategies in response to the pandemic shutdown. As they face the possibility of never going back to what independent bookselling used to be, Jason Purcell and Kelly Dyer share their hopes and struggles as indie booksellers during this special time. If there is only one way to enter the post-pandemic future, let us still preserve the love for each other. Produced by Sophia Yang.

Updates on the University of Alberta Fall 2020 Planning Group, summer camps, and federal support for students. Produced by Sophia Yang.

Updates for students applying at the University of Alberta. Produced by Sophia Yang.

Updates on how Covid-19 changes will affect University of Alberta students. Produced by Sophia Yang.

It's the end of the season and we decide to make a wrap for you. In this episode, That's Food producers Dan Collera, Ralph Garcia, Katelin Karbonik, and Sophia Yang sit around in CJSR's studio A and wrap up the first season of our show. This is the bonus episode where you can learn the facts and myths of That's Food, for example, why is the show called "That's Food" anyway? As That's Food reveals the backstory to Edmonton's food, That's A Wrap reveals the backstory to That's Food. (If you're also into Star Wars, you may already knew that the name of this episode rhymes with that famous line of Admiral Ackbar.)

What is Edmonton's signature food? In this episode, Sophia Yang goes on a trip to try three popular foods in Edmonton, nominated by her friends from University. Rating the foods for their originality, taste, and Edmonton-ness, which one of the foods would win Sophia's heart? And, most importantly, which one of the dishes makes her feel most like an Edmontonian?

To find out how businesses that sell cold food in Edmonton survive our signature wintertime, producer Sophia Yang sets her sights on Kind Ice Cream in Edmonton's Ritchie neighbourhood. In this episode, Sophia interviews Paula Shyba, co-founder of Kind Ice Cream, about ice cream stories in winter Edmonton. Is our city ready to embrace more ice cream and waffle cones? Check out this episode (with a mind blowing fact about ice cream/Edmonton)!

Did you eat breakfast this morning? How about yesterday? Does it matter? Come meet Evan Armstrong, Bria Wong, and Mackenzie Walker, as we talk to them about their different breakfast habits and opinions; diving into the mystery of the morning meal one slice of toast at a time. Produced by Kyla Wong and Sophia Yang.