WEBVTT Kind: captions; Language: fi 1 00:00:00.860 --> 00:00:02.920 Thank you. Thank you. 2 00:00:02.920 --> 00:00:05.090 Sen jo. 3 00:00:05.090 --> 00:00:10.740 Se on hello everyone jari lindroos midot toivonen. 4 00:00:10.740 --> 00:00:18.800 And we are here, drive your presentation about the future of AI bastuments. 5 00:00:18.800 --> 00:00:26.250 Presentation will cover prefer description of AI and some of its possible applications. 6 00:00:26.250 --> 00:00:31.590 The were going to discuss the current trends in AI little bear 7 00:00:31.590 --> 00:00:38.500 about effect of AI entinen som constructions. 8 00:00:38.500 --> 00:00:44.010 Se first eii and its applications. 9 00:00:44.010 --> 00:00:49.980 S may now there school different offices in computer science, artificial 10 00:00:49.980 --> 00:00:54.650 intelligence for AI iso branch of computer science. 11 00:00:54.650 --> 00:00:59.630 Thames to create intelligent machinesher capable of performing 12 00:00:59.630 --> 00:01:05.200 tass typically record human intelligence. 13 00:01:05.200 --> 00:01:11.390 X art fordstens visual perception, speech recognition, decision making and problem solving 14 00:01:11.390 --> 00:01:18.590 clear related to, say tunes, machine learning and exploring machine learning reforst 15 00:01:18.590 --> 00:01:25.050 modelslerin from the training data without exclusive kiven ross. 16 00:01:25.050 --> 00:01:31.960 Diploning or deep neural networks in love, especially dipper architects, consists 17 00:01:31.960 --> 00:01:41.180 of multitouch of players and utilization of very large training data. 18 00:01:41.180 --> 00:01:48.540 Anders here pictures, the future visual sound neural networks work on the left. 19 00:01:48.540 --> 00:01:56.650 The crash of the verisinble, the neural network that one hidden layer age, the input 20 00:01:56.650 --> 00:02:03.480 spring fest tuned work with one or several heidän layers and lentäneetgers old and output 21 00:02:03.480 --> 00:02:11.290 we andreas city dd sul have lot more players and are more complicated. 22 00:02:11.290 --> 00:02:14.110 Architecture. 23 00:02:14.110 --> 00:02:19.370 Win convert two architecture expressed in here. 24 00:02:19.370 --> 00:02:27.470 And on the right we haven example, image import two visualisointien ens work and the visibleyer 25 00:02:27.470 --> 00:02:35.760 hash pictures of colors directly human ai and works asti input and players 26 00:02:35.760 --> 00:02:42.590 there contribute to more find great information bing based on the network teemakin possible 27 00:02:42.590 --> 00:02:52.560 prosessi dada match with several levels of abstraktion. 28 00:02:52.560 --> 00:02:58.840 More precise ly classic machine learning modules learn from and design features 29 00:02:58.840 --> 00:03:04.440 the dar drawn from the inputda tismalleen sten created mapping from the 30 00:03:04.440 --> 00:03:09.290 features in order to provide the output data. 31 00:03:09.290 --> 00:03:13.830 Se on itse freddy simple madal deploying mads. 32 00:03:13.830 --> 00:03:21.110 However, futurice representation learning away than design features and totta modules 33 00:03:21.110 --> 00:03:27.340 learned simple features of the data theon with the additional hidden layers taylorin 34 00:03:27.340 --> 00:03:35.190 more abstract features from the dark and from peace abstract feature mapping features 35 00:03:35.190 --> 00:03:45.200 mapping are formed the walk in port. 36 00:03:45.200 --> 00:03:51.710 Heartuter swit boxin blackbox future explained difference between. 37 00:03:51.710 --> 00:03:58.950 Tis rupea depending systems with rupes systems, we have expensive britann ross. 38 00:03:58.950 --> 00:04:05.630 The algoritmi flows se on natural wikin track see when and how the values of 39 00:04:05.630 --> 00:04:13.790 paramedic change the code running so we defining mads orsonce features of 40 00:04:13.790 --> 00:04:20.600 the deal bingoern and the moralstra, future sound, etcetera cowen training deploy 41 00:04:20.600 --> 00:04:24.750 single we are mainly of war of the imports and outs. 42 00:04:24.750 --> 00:04:31.650 No the way modelers mining how it comes, the conclusion sor kives predictions, 43 00:04:31.650 --> 00:04:39.440 il happens in the dark, taas the name blackbox. 44 00:04:39.440 --> 00:04:45.740 Ja se jäi systems become complex understanding the decision making prosessissa becomes 45 00:04:45.740 --> 00:04:54.080 crucial premantura deller about black boxes and how challengesplayn hawaii sistem 46 00:04:54.080 --> 00:05:01.440 srivations explainedble, am so dresseshu by developing methods and technics the provide 47 00:05:01.440 --> 00:05:10.530 transparency and the prebility building trustin ei jäisestä widell. 48 00:05:10.530 --> 00:05:14.760 Partsille oli en files li healthcare financial. 49 00:05:14.760 --> 00:05:23.020 Tällöin force mand were critical vision surfing mate. 50 00:05:23.020 --> 00:05:29.740 So before you think IMA ll system and the future and the traditional way of training, 51 00:05:29.740 --> 00:05:36.570 air mads inves using cards, datasets training prosess tätä opens in sopiwa sector 52 00:05:36.570 --> 00:05:43.110 and superwood manner and supervision learning the mahdollis provided with input output 53 00:05:43.110 --> 00:05:49.920 cars and lunch mape input the core spanking output. 54 00:05:49.920 --> 00:05:57.810 Siis prosessi records many label data mining tuman sneaker have had the day deal with 55 00:05:57.810 --> 00:06:05.340 text answers before starting the train, the model the model lens during training process, 56 00:06:05.340 --> 00:06:13.840 the general general from this label examples and make predictions on new anssin dada 57 00:06:13.840 --> 00:06:20.220 example of classification task the images of cards. 58 00:06:20.220 --> 00:06:23.520 Oikeasti import and the names of the records act as 59 00:06:23.520 --> 00:06:30.610 labels or the design output indicate. 60 00:06:30.610 --> 00:06:35.370 Nata learning ei sköld unsubvist learning. 61 00:06:35.370 --> 00:06:41.560 Niin antsu learning the maple leafs, parents and structures of the data without any label 62 00:06:41.560 --> 00:06:48.870 information, for example, in flashing the distance of date points to the cluster centre 63 00:06:48.870 --> 00:06:57.110 point source, central alcatel intuitive intuition www.ld protection 64 00:06:57.110 --> 00:07:05.190 of tweets caster is the point belongs two, for example, this picture centres. 65 00:07:05.190 --> 00:07:12.960 Market with wide crush. Turbine blasters overol. 66 00:07:12.960 --> 00:07:23.710 Andrew's burning camber useful for tass life feature extraction or data compression. 67 00:07:23.710 --> 00:07:30.040 Son next we have some of the main domains of AI. 68 00:07:30.040 --> 00:07:36.120 Vanhusten is natural language processing on LPN short fokuksessa on meikkien, computers 69 00:07:36.120 --> 00:07:44.240 understand interest and generate human language edin walls täss like massage translation, 70 00:07:44.240 --> 00:07:53.450 toksiset itsection, text, some recreation and recognition jericho on open source 71 00:07:53.450 --> 00:08:00.520 text dataset consists of english french sentences, for example. 72 00:08:00.520 --> 00:08:08.840 Niin english are alone is translated some 4 että schönau teette sen siis ard original 73 00:08:08.840 --> 00:08:17.230 scrap from the web and the english french sound to be collin two each other and cetis 74 00:08:17.230 --> 00:08:26.350 very large concept of around twenty two miljoonan samples. 75 00:08:26.350 --> 00:08:35.010 Natur mayn domain is computer vision oreja insert images computers to extract 76 00:08:35.010 --> 00:08:43.130 min for information from image or videoday ydinalue sanchez objektit action 77 00:08:43.130 --> 00:08:52.600 images classification image segmentation, facial recognition and visual siinä understanding. 78 00:08:52.600 --> 00:08:59.480 Example en america setting record power 100. sad connecting of americ images of brains and 79 00:08:59.480 --> 00:09:10.150 classified the two different categories defrag having schumer or no tour. 80 00:09:10.150 --> 00:09:18.230 Ven we have rainforest learning for it was the training of nayaged 81 00:09:18.230 --> 00:09:26.560 to make cecil visions true interaction with the warmment agent lens actions 82 00:09:26.560 --> 00:09:32.260 maximissa records signal based on feedback tai siis research research from the 83 00:09:32.260 --> 00:09:39.750 infant RLS applicationsin gambling robotics recommendations systems. 84 00:09:39.750 --> 00:09:46.510 En olet syönyt muassa viikossa for example entis one coding competition decoder 85 00:09:46.510 --> 00:09:53.390 switch ready agence deadly football NS tubecon football game the objective 86 00:09:53.390 --> 00:10:00.730 was to have your team the score morten tai accept the resource bittinen render 87 00:10:00.730 --> 00:10:08.110 dh space freddy fordbles mutation. 88 00:10:08.110 --> 00:10:15.420 The last one easy odile ei näy ed focuses on the analysis, processing and understanding of 89 00:10:15.420 --> 00:10:23.510 odin data including speech recognition, music, analysis of business and more. 90 00:10:23.510 --> 00:10:28.320 For example, in speech recognition spostilla with convert intervention 91 00:10:28.320 --> 00:10:33.980 text idin walls technics like the match with recognition and voice 92 00:10:33.980 --> 00:10:37.870 command recognition, speed, recognitionisuus. 93 00:10:37.870 --> 00:10:43.270 Virtual assistance transcription services, voisi control, ld systems and 94 00:10:43.270 --> 00:10:51.720 voice biometrich annin finlanders project lahjoita puhetta speech finnish 95 00:10:51.720 --> 00:10:59.950 dayspin collected advance finnish recognition. 96 00:10:59.950 --> 00:11:07.960 We are you only lupaus lil ***** about current state of AI so artificial intelligence, 97 00:11:07.960 --> 00:11:16.240 magnificent progress in recent cs and general motors chachi release last year 98 00:11:16.240 --> 00:11:20.870 or the forefront of the progress showing over one point seven miljardin user 99 00:11:20.870 --> 00:11:25.940 billion users in itre anders ry. 100 00:11:25.940 --> 00:11:32.900 Ei itse technology on great integration into stoch healthcare finance, 101 00:11:32.900 --> 00:11:41.080 transportation entertainment from voisi sitten alexa thureson algorithms 102 00:11:41.080 --> 00:11:48.760 just streaming services ei ISU daily daily lives. 103 00:11:48.760 --> 00:11:54.290 Itseäsi enable significantly dvdmentin natural language processing, computer 104 00:11:54.290 --> 00:12:01.910 vision and other fields of machine learning wellness robotics. 105 00:12:01.910 --> 00:12:07.100 Anteeksi slaidissa but something released today maybe jari 106 00:12:07.100 --> 00:12:12.590 crowe joo sow the breaking news for today. 107 00:12:12.590 --> 00:12:14.630 Somebody has not yet heart. 108 00:12:14.630 --> 00:12:22.450 Google reveal the newest large language model jimmy antis sai multimodal 109 00:12:22.450 --> 00:12:28.040 break tru andres fordissa newer tai multimodaalinen traction kanssa 110 00:12:28.040 --> 00:12:31.090 unlike traditional language models. 111 00:12:31.090 --> 00:12:39.500 Gemini, kansi integrated pest, images, audio, video code and disvasta first 112 00:12:39.500 --> 00:12:45.370 model out perform human experts on massive multitasking language understanding 113 00:12:45.370 --> 00:12:49.440 benchmark switch, one of the most popular states. 114 00:12:49.440 --> 00:12:57.820 No problem solving of you and it also sur pasta gt for model in every 115 00:12:57.820 --> 00:13:02.240 text and the multimedia benchmark except for the helasvuo. 116 00:13:02.240 --> 00:13:08.660 Benchmark switch for evaluation, communications, reasoning for every day tass. 117 00:13:08.660 --> 00:13:17.060 And googlella has released modelling thesis ultra and nano 118 00:13:17.060 --> 00:13:24.910 all for different scalability purposes. 119 00:13:24.910 --> 00:13:32.360 Next will about current trends. I. 120 00:13:32.360 --> 00:13:39.480 So the man technology behind the many of the corn top models, and even the newest 121 00:13:39.480 --> 00:13:48.680 google cmy ist transformer tää transformers, mrs grand breaking modalarkkitehtuurin 122 00:13:48.680 --> 00:13:56.180 ennen and very first manly just for täss light machine translation watch later 123 00:13:56.180 --> 00:13:59.870 thanbyn also juutilaisten computer vision. 124 00:13:59.870 --> 00:14:07.800 Nauti har presidentin ever multimodal capabilities, no deal and videos osuu. 125 00:14:07.800 --> 00:14:14.440 Tämän benefit of the architecture ist attention bäst algoritmi. 126 00:14:14.440 --> 00:14:19.650 Että me tismaksi tää possible for the model to. 127 00:14:19.650 --> 00:14:27.820 Learn features that arch maptin long distance and able to calculate mm with 128 00:14:27.820 --> 00:14:35.840 less computational efficiency and hearing the picture wc related words. 129 00:14:35.840 --> 00:14:43.060 Ja evening after the fairway distance tag still be map together. 130 00:14:43.060 --> 00:14:46.940 En tiedä siis tää main difference from the traditional deep 131 00:14:46.940 --> 00:14:55.890 neural networks th ben justiin the past. 132 00:14:55.890 --> 00:14:57.950 Se on. 133 00:14:57.950 --> 00:15:03.900 Somaattisten idästä dead muodostat SBN best on transformers. 134 00:15:03.900 --> 00:15:12.530 Bert fort for by direction and core presentations for transformers, GBT generator, 135 00:15:12.530 --> 00:15:20.810 free trend transformer alsovision transformer and the west jimmy diesel 136 00:15:20.810 --> 00:15:28.600 morales, different variations for advanced language understanding urlang, 137 00:15:28.600 --> 00:15:32.040 text generation and transfer learning. 138 00:15:32.040 --> 00:15:35.700 An tärkeämpi different types of models further developed 139 00:15:35.700 --> 00:15:38.140 for training based on this models. 140 00:15:38.140 --> 00:15:46.360 For example, on finnish language, theresa finnbert model with based on the bert backer vaatii 141 00:15:46.360 --> 00:15:54.210 taas trendi on levit finnish institute of the original bertha base english. 142 00:15:54.210 --> 00:16:02.170 Osa piti messun familar tuolla **** off chachi björ getre 143 00:16:02.170 --> 00:16:08.870 get for and presenter tai buff generate model. 144 00:16:08.870 --> 00:16:15.050 Also the final example sta vision transformer model presenting 145 00:16:15.050 --> 00:16:18.900 the doll ior stable diffusion top model. 146 00:16:18.900 --> 00:16:27.900 Www.create, nice work of art from just promoting suurta tai pop keywords. 147 00:16:27.900 --> 00:16:34.870 Zoo mä pidän about promptting prompt pingistä process of designing 148 00:16:34.870 --> 00:16:39.430 prompt gite guide and direct language model. 149 00:16:39.430 --> 00:16:45.210 Tukin generated wanted to put and siis väri crucial 150 00:16:45.210 --> 00:16:50.540 off juutilaisen the language correctly. 151 00:16:50.540 --> 00:16:56.270 Carefully construct prompt provide language model with necessary record 152 00:16:56.270 --> 00:17:01.420 text instructions and information product out pot. 153 00:17:01.420 --> 00:17:08.080 Why one ***** disneyn cloud clearly outlined what the askissa että 154 00:17:08.080 --> 00:17:13.440 hand for example samanväriset text of something. 155 00:17:13.440 --> 00:17:21.220 Alright anchor discussion about this and we were provided 156 00:17:21.220 --> 00:17:24.930 relevant backround informations and examples. 157 00:17:24.930 --> 00:17:33.080 Two further give the language concepts and more understanding ovat 158 00:17:33.080 --> 00:17:40.020 must fall elisa about interesting and defining eksperimentin the different 159 00:17:40.020 --> 00:17:44.040 prompt and refine them based on the language models. 160 00:17:44.040 --> 00:17:51.370 Response tuo optimaalista und resorts. 161 00:17:51.370 --> 00:17:57.990 Tuo sheratonve referencetyä sables of debt morning 162 00:17:57.990 --> 00:18:02.380 we new dayta org content generated. 163 00:18:02.380 --> 00:18:10.490 Using existing data häntä go list product close to the original input. 164 00:18:10.490 --> 00:18:12.290 Niin siinä yritti. 165 00:18:12.290 --> 00:18:17.540 Ei jäi siis teep morning algoritmeissa are just to learning paths and features 166 00:18:17.540 --> 00:18:25.790 in the dayta watch may consists of code, text, images ortio video or any 167 00:18:25.790 --> 00:18:34.230 other day tours and his generate jäi hänen airbnb uni model are multimedia 168 00:18:34.230 --> 00:18:39.530 ja niin unimedel online data types just soccer. 169 00:18:39.530 --> 00:18:46.600 Teksti teksti generation or images image image generation. 170 00:18:46.600 --> 00:18:51.600 Wen toki bot multimedia liity vie juu several moons link 171 00:18:51.600 --> 00:18:58.390 text image teksti speak generations. Sing from the examples. 172 00:18:58.390 --> 00:19:07.700 Trumpting happy hippo, flying the sky and the siksi magyar what model things? 173 00:19:07.700 --> 00:19:13.940 The prompt looks like. 174 00:19:13.940 --> 00:19:18.480 Soo bit more bot lords language model senttiä diffusion 175 00:19:18.480 --> 00:19:25.210 models edelleen ms like GBT for the buff. 176 00:19:25.210 --> 00:19:30.920 Deep burning model that been trained on massive of data can generate 177 00:19:30.920 --> 00:19:37.050 human light text common uses Marin groundsring questions some rising 178 00:19:37.050 --> 00:19:46.460 translateting generating soratien blocker. Doing your homework? 179 00:19:46.460 --> 00:19:55.430 And other models diffusion model sar osuva tai generated modules dating and significant 180 00:19:55.430 --> 00:20:03.070 attention in the field of watching learning pikaisesti, siis models by design to generate 181 00:20:03.070 --> 00:20:08.730 väri realistic samples mennä prosecco diffusion prosess. 182 00:20:08.730 --> 00:20:15.880 En ties diffusion model slide down your stable diffusion. 183 00:20:15.880 --> 00:20:24.600 Learn from vasta month of data theben trend on meni meni metsään artsvit 184 00:20:24.600 --> 00:20:26.400 tää. 185 00:20:26.400 --> 00:20:33.830 Prompt off meni meni different taakse categories related työtä ary am and we have the 186 00:20:33.830 --> 00:20:42.120 belly tuo signature realistit text or art images and also hyvän music. 187 00:20:42.120 --> 00:20:45.530 Niin pitch switch tower, exciting possibility. 188 00:20:45.530 --> 00:20:50.910 Meni creative applications. 189 00:20:50.910 --> 00:20:58.360 So but juvenes break there SBN actually juutilaissing täällä arts angeles moralesin 190 00:20:58.360 --> 00:21:06.880 green forcen turning EU reka NA agen developed by vidia. 191 00:21:06.880 --> 00:21:14.180 Vitsi vitsi primary function vastuu trend robots superfood kompleksistasch but 192 00:21:14.180 --> 00:21:20.820 ja induced by automatically generating reward algoritmit witch niistä meidän 193 00:21:20.820 --> 00:21:25.620 principal for training growth from greenford morning. 194 00:21:25.620 --> 00:21:32.270 So basically the agent twitchin disc case Vaasan GPT for. 195 00:21:32.270 --> 00:21:39.150 Itse se ei jäi tapsin tätä model hän tee generative ei jäi rights the software 196 00:21:39.150 --> 00:21:44.830 code täält rewards the robots for the ring forsman learning and world is 197 00:21:44.830 --> 00:21:52.330 fascinating start this eurekan tosin actually rek warrenia specific promptting 198 00:21:52.330 --> 00:21:58.130 or any pre defined rewe varten place. Mitkä on? 199 00:21:58.130 --> 00:21:59.930 Niinpä niin. 200 00:21:59.930 --> 00:22:02.900 Corporate human feedback to the reward algorithm what is 201 00:22:02.900 --> 00:22:08.690 completely just based on the prompt GB defor? 202 00:22:08.690 --> 00:22:16.790 Onhan tää robotsinti seuraa wordtu performed nearly hurtig different tasks witch blues räpit benzinning 203 00:22:16.790 --> 00:22:23.540 trick the base gröning walking opening rovers and tossa balsa and such. 204 00:22:23.540 --> 00:22:26.460 Oot also what? 205 00:22:26.460 --> 00:22:33.770 GBT for hasbeen just is to play minecraft and this is basically. 206 00:22:33.770 --> 00:22:41.310 Base on tässä ei mekanismi but indicate the game and cheek for basic communicate 207 00:22:41.310 --> 00:22:45.610 with shower and providing the current state of the game. 208 00:22:45.610 --> 00:22:48.470 Tota cheek before *****. 209 00:22:48.470 --> 00:22:55.370 Air critics on informo peter the program archives tätä ask hän hinat edition ift 210 00:22:55.370 --> 00:23:01.610 task files it will provide kritiik church justinin how to complete task, for example, 211 00:23:01.610 --> 00:23:08.840 how autobild course for missingeson wood go pants tree. 212 00:23:08.840 --> 00:23:16.010 What next? Stop about ethics jae. 213 00:23:16.010 --> 00:23:23.990 So evento many people justice generateve scsi piti gizmodon 214 00:23:23.990 --> 00:23:29.140 still product resource combe facial incorrect. 215 00:23:29.140 --> 00:23:37.400 Antis what wereface ei tai hallusinaation and this happens generation 216 00:23:37.400 --> 00:23:41.380 tatar trend on such marssiva mount data. 217 00:23:41.380 --> 00:23:49.620 Data included both the facial infoo and also increase information witch in 218 00:23:49.620 --> 00:23:51.420 resort. 219 00:23:51.420 --> 00:23:56.740 Caldes muodostui generation tekstit false flag. 220 00:23:56.740 --> 00:24:02.750 Siinä siis. Sumari säätiön palon tässä screen. 221 00:24:02.750 --> 00:24:09.900 Väestö suomalaisia linkittää dosentiksi just just bastont link. 222 00:24:09.900 --> 00:24:15.800 And also wild. This can have some creative applications. 223 00:24:15.800 --> 00:24:24.600 The post significant ethical concernsches tai mies information disinformaation. 224 00:24:24.600 --> 00:24:29.940 En discord of agereitä, että hallusinaation cool be creator 225 00:24:29.940 --> 00:24:34.620 spread falls or miss clearing information wide. 226 00:24:34.620 --> 00:24:40.270 Kyllähän potentiaali manipuloi public opinion on course harm. 227 00:24:40.270 --> 00:24:47.410 No se on this hallusinaation school reflect amplifier beach in training daytä 228 00:24:47.410 --> 00:24:57.930 leading to discrimination output stat canal björn full. 229 00:24:57.930 --> 00:25:06.350 Soul ja hallusinaation on one example of the limitationste ja systems may all the 230 00:25:06.350 --> 00:25:15.770 show this important to consider letician using AI dis minst center race face 231 00:25:15.770 --> 00:25:22.620 when design this and designing and implementingis ja systems visual osu. 232 00:25:22.620 --> 00:25:30.610 The consideration certain matters like privacy, basen jobs placement. 233 00:25:30.610 --> 00:25:38.070 Minun ****** adress concerns to ensure responsible and fair use of technology. 234 00:25:38.070 --> 00:25:43.690 Visual asbestin slide haglund ensure tätä ja system Priority 235 00:25:43.690 --> 00:25:48.000 chima webbiin liittää human välitys. 236 00:25:48.000 --> 00:25:51.850 Ovat mekanismi shouldeen place prevention system from 237 00:25:51.850 --> 00:25:56.310 coaching farmorbet rating yes and more. 238 00:25:56.310 --> 00:26:04.820 Promote transparency and accountability in AI decision making. 239 00:26:04.820 --> 00:26:11.250 Se on pajassa ennen stance criticalation, että niistä beatrice. 240 00:26:11.250 --> 00:26:18.530 Basiskan rise from best training daytä or algoritmit byers leading to onfer 241 00:26:18.530 --> 00:26:25.600 art comes and michiganin bass records actionia divers and representatives 242 00:26:25.600 --> 00:26:32.310 training day we detection and fairness over algorithms. 243 00:26:32.310 --> 00:26:37.040 Ei ja ja applications often invalid collection house hand store 244 00:26:37.040 --> 00:26:42.200 of personal databach races meni privacy concerns. 245 00:26:42.200 --> 00:26:49.340 Walsall crucial tuen suurta responsible and ethical data, which may include informed 246 00:26:49.340 --> 00:26:55.050 consent data, anonymisation and secure data security measures. 247 00:26:55.050 --> 00:27:00.820 Istuu protect users individuals privacy rights. 248 00:27:00.820 --> 00:27:08.490 The way tu hands tai problems in contrast to machine learning, ice machine 249 00:27:08.490 --> 00:27:14.960 underning witches, the process of removing or modify data or knowledge 250 00:27:14.960 --> 00:27:18.480 from the already trend schillerin model. 251 00:27:18.480 --> 00:27:24.480 Diesel offers meni adventist siis over just ret raining model. 252 00:27:24.480 --> 00:27:31.100 Pikaiset svetari koostui and lähteekö väri väri long time trendissä large model 253 00:27:31.100 --> 00:27:41.190 show juutilaisen best of technics verin port in the field. 254 00:27:41.190 --> 00:27:49.250 Soul one type of research goin oninea, texas ja limente gt refer 255 00:27:49.250 --> 00:27:58.560 to lining ei olisi systems with human välillä sand goes len short day active way tai isä benefitcial. 256 00:27:58.560 --> 00:28:08.080 Every body and etsi cala this to prevent on intent consequences and potential risks. 257 00:28:08.080 --> 00:28:13.870 Ja siistem mieheltä control for the reaction established clear lines 258 00:28:13.870 --> 00:28:20.790 of responsibility, contability inceptioncial particularille en domains 259 00:28:20.790 --> 00:28:24.780 ja systems make the critical decisions. 260 00:28:24.780 --> 00:28:30.600 Warsaw transparency explain ability in decision making prosessissa 261 00:28:30.600 --> 00:28:40.830 enable scouting of the deputy and user trust. 262 00:28:40.830 --> 00:28:46.690 Ja se on vaan exempel off controllercial house faye vendée. 263 00:28:46.690 --> 00:28:53.250 Ei jäi muodoista, että haben trained on the art pictures dolly täältä originally 264 00:28:53.250 --> 00:28:59.570 from artist that may have not given permission to just for art. 265 00:28:59.570 --> 00:29:02.610 Niin understand the belt tai artistit. 266 00:29:02.610 --> 00:29:07.150 Me ei vaan prestige uusi tarjous of the art in order to 267 00:29:07.150 --> 00:29:11.370 preserve the possible future opportunities. 268 00:29:11.370 --> 00:29:15.850 Fortis teräsbyn develop tiskiin of technology SW ei tuo 269 00:29:15.850 --> 00:29:19.790 counter arctis taipu wanted data scripting. 270 00:29:19.790 --> 00:29:27.270 For instance, saa program tai alterran imagine way trip stay muodolla. 271 00:29:27.270 --> 00:29:34.950 Vesikeli fréjus program willard small amount of noise, tota image. 272 00:29:34.950 --> 00:29:40.440 Tai siis minimalismi hieman näe palatsit vielä riley 273 00:29:40.440 --> 00:29:48.360 hinderta performance softia ja modo. 274 00:29:48.360 --> 00:29:54.980 Sonax, we have sun constructions. 275 00:29:54.980 --> 00:30:03.100 So about the possibilities tai lay ei research ei will be integrated to 276 00:30:03.100 --> 00:30:10.140 every day life with smart homes, soft ravin cars, virtual assistance and 277 00:30:10.140 --> 00:30:16.060 power device in hansin convenience and infections. 278 00:30:16.060 --> 00:30:23.530 Eilisistä will super understand and generate human language sweater conversation. 279 00:30:23.530 --> 00:30:30.270 Ations, translation services and voice systemce and radar tän replaced 280 00:30:30.270 --> 00:30:35.860 comments ja vilmos likely comment human capabilities and collaborate 281 00:30:35.860 --> 00:30:39.370 with astin solving complex problems. 282 00:30:39.370 --> 00:30:46.310 And ongoing research will focus on improving capabilities, driving innovation 283 00:30:46.310 --> 00:30:51.320 and exploring of frontiers tai exploringble aijai. 284 00:30:51.320 --> 00:31:00.120 Advanced neural network architecture and quantum computing. 285 00:31:00.120 --> 00:31:02.230 Sen. 286 00:31:02.230 --> 00:31:09.630 Me ei vie about the bid for the future of AI hold siemens proms, pot osui cs 287 00:31:09.630 --> 00:31:17.460 responsible and secure moment ei aiveloments on hapen ja void but it will be 288 00:31:17.460 --> 00:31:24.990 continued shaped lives factions like effica considerationns se sille choices, 289 00:31:24.990 --> 00:31:31.440 public public perception and regulatory frameworkks. 290 00:31:31.440 --> 00:31:37.520 Se on furness transparency ja account billy the soul, super priorityistin, future 291 00:31:37.520 --> 00:31:46.960 research to possible lies and criminalation present in ei aio systems. 292 00:31:46.960 --> 00:31:49.620 Se on thank you all for listening. 293 00:31:49.620 --> 00:31:55.380 And there sun references. 294 00:31:55.380 --> 00:31:59.930 Maybe we have some time left. 295 00:31:59.930 --> 00:32:08.680 Shreeso are work that we have been doing in the form of video ortio. 296 00:32:08.680 --> 00:32:15.630 The time just remember sharing the video unity shorty audio as well. 297 00:32:15.630 --> 00:32:18.270 OK click when you. 298 00:32:18.270 --> 00:32:24.690 Inter share screen lowry jotenkin this place de clichy audio. 299 00:32:24.690 --> 00:32:44.690 OK. 300 00:34:07.010 --> 00:34:29.150 Siitä satsausta täysillä. Mä jotenkin check hei. 301 00:36:21.280 --> 00:36:26.400 Sothys video on specifically about this infrastructure project. 302 00:36:26.400 --> 00:36:35.300 We have the working on antista source exempel using my or more specifically 303 00:36:35.300 --> 00:36:41.100 name direction for archive taida and then we have another video, 304 00:36:41.100 --> 00:37:01.100 may be wicked get the voice tiesimme. 305 00:37:08.340 --> 00:37:17.620 I'll live streaming. Watch now now. 306 00:37:17.620 --> 00:37:24.510 Et smoothi just gay itse glow from. 307 00:37:24.510 --> 00:37:28.170 No cry department, the cars beyond the surface and 308 00:37:28.170 --> 00:37:39.220 on what the voice shaping experience. 309 00:37:39.220 --> 00:37:58.500 The real thing, the cover, push the pois. 310 00:37:58.500 --> 00:38:05.880 This way we find the true story. 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Thank you so much. Thank you.